Integrated Crop Management Conference Proceedings
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Proceedings of the 20th Annual Integrated Crop Management Conference December 10 – 11, 2008 Iowa State University Ames, Iowa Agribusiness Education Program 20th Annual Integrated Crop Management Conference December 10 – 11, 2008 Iowa State University Ames, Iowa Proceedings Table of Contents Speaker contact information......................................................................................................... 7 Crop management 1. Iowa climate: A century of change ......................................................................................... 9 Elwynn Taylor, Agronomy, Iowa State University. 2. Resources needed for record-breaking soybean yields........................................................... 17 Larry Purcell, Crop, Soil and Environmental Sciences, University of Arkansas. 3. No-tillage soybean production in Iowa................................................................................. 33 Palle Pedersen, Agronomy, Iowa State University. 4. For crops it’s rotation, rotation, rotation! The sustainability of the corn-soybean cropping system. ........................................................................................... 41 Prepared by Brent A. Pringnitz, coordinator, Agribusiness Education Program, Iowa State University Extension Joe Lauer, Agronomy, University of Wisconsin-Madison). 5. Corn plant populations: A critical component in the yield equation .................................... 43 Roger Elmore and Lori Abendroth, Agronomy, Iowa State University. Agribusiness Education Program Iowa State University Extension 2104B Agronomy Hall Ames, Iowa 50011-1010 Phone: (515) 294-6429 FAX: (515) 294-1311 aep@iastate.edu www.aep.iastate.edu 6. Predicting yield before harvest: How does the USDA forecast corn and soybean yield? . ...... 49 Greg Thessen, USDA-National Agriculture Statistics Service (NASS). 7. Sorting through the forage choices for Iowa producers......................................................... 53 Stephen Barnhart, Agronomy, Iowa State University. 8. Practical considerations in developing bioenergy.................................................................. 57 Emily Heaton, Agronomy, Iowa State University. 9. Practical considerations in developing bioenergy.................................................................. 59 Matt Darr, Agricultural and Biosystems Engineering, Iowa State University Copyright © 2008 by Iowa State University 10.Progress in using near infrared grain analyzers (NIR) to measure amino acids in corn.......... 63 Various agricultural products are mentioned in the articles contained in this proceedings. Mention of trade names does not imply endorsement of one product over another, nor is discrimination intended against any similar product not named. … and justice for all The U.S. Department of Agriculture (USDA) prohibits discrimination in all its programs and activities on the basis of race, color, national origin, gender, religion, age, disability, political beliefs, sexual orientation, and marital or family status. (Not all prohibited bases apply to all programs.) Many materials can be made available in alternative formats for ADA clients. To file a complaint of discrimination, write USDA, Office of Civil Rights, Room 326-W, Whitten Building, 14th and Independence Avenue, SW, Washington, DC 20250-9410 or call 202-720-5964. Issued in furtherance of Cooperative Extension work, Acts of May 8 and June 30, 1914, in cooperation with the U.S. Department of Agriculture. Jack M. Payne, director, Cooperative Extension Service, Iowa State University of Science and Technology, Ames, Iowa. Connie Hardy, Value Added Agriculture Program, Iowa State University. Prediction of fermentable starch content by near-infrared spectroscopy................................ 69 Allison Burgers, Food Science and Human Nutrition, Iowa State University. 11.Methodology to insure U.S. genetically modified (GM) grain sales into approved foreign markets: Integrating ISO traceability standards with agricultural quality management systems............................................................................................................ 75 Gregory Bennet, Grain Quality Laboratory, Iowa State University. 4 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 5 12.Grain storage, storage cost and training module................................................................... 83 29.Update in weed management 2009: Has the silver bullet been developed? ........................ 157 13.Grain, oilseed and biofuel outlook for 2009......................................................................... 83 Nutrient management 30.Fertilizer costs and crop production in 2009...................................................................... 225 14.Food and fuel: Enough grain but we need more processing.................................................. 83 Charles Hurburgh, Agricultural and Biosystems Engineering, Iowa State University. Factors that determine the cost of food................................................................................. 83 Chad Hart, Economics, Iowa State University. 15.ACRE and SURE: Two new commodity programs under the 2008 Farm Bill......................... 83 ft William Edwards, Economics, Iowa State University. 16.Changes in costs of production............................................................................................. 83 Mike Duffy, Economics, Iowa State University. 17.Organic agriculture in Iowa: Economics in the era of ethanol............................................... 83 Kathleen Delate, Agronomy, Iowa State University; Craig Chase, Economics, Iowa State University. Pest management 18.Theory and practice of Integrated Pest Management in the 21st century............................... 89 ra Richard Pope and Marlin Rice, Entomology, Iowa State University. David Asbridge, Doane Advisory Services. 31.Managing nitrogen for optimum profit and minimum environmental loss.......................... 231 Gyles Randall, Southern Research and Outreach Center, University of Minnesota. 32.Comparison of spring-applied ESN and urea as sources of nitrogen for corn production.... 241 Randy Killorn, Agronomy, Iowa State University. 33.Fertilizing crops in the new price age: nitrogen................................................................... 255 John Sawyer, Agronomy, Iowa State University. ft Chad Hart, Economics, Iowa State University. Micheal D. K. Owen, Agronomy, Iowa State University. 34.Fertilizing crops in the new price age: potassium................................................................ 255 Antonio Mallarino, Agronomy, Iowa State University. 35.Manure: The new commodity............................................................................................. 255 Angela Rieck-Hinz, Agronomy, Iowa State University. Soil and water management 36.Impacts of extreme precipitation events on performance of conservation practices............. 259 Matt Helmers, Agriculture and Biosystems Engineering, Iowa State University. ra Howard Shepherd, Iowa Grain Quality Initiative, Iowa State University. 19.Soybean aphid and potato leafhopper thresholds: Revisiting IPM decision support for soybeans and alfalfa in a high value field crop commodity rotation....................................... 93 37.Effect of cover crops in reducing nitrate-nitrogen leaching in Iowa..................................... 265 20.Focus on insects: A review of the top 5 research articles in agricultural entomology............. 97 38.Tillage considerations on previously flooded soils............................................................... 279 21.Aphid resistant soybeans: Will they prevent soybean aphid outbreaks?.............................. 105 39.Tillage and crop rotation management impact on yield and soil quality.............................. 295 22.What have we learned from five years of managing soybean aphids with insecticides? ...... 109 40.Using GIS technology for Iowa pesticide distribution and transport modeling.................... 295 Marlin Rice, Entomology, Iowa State University. Matt O’Neal, Entomology, Iowa State University. d Kevin Johnson, Entomology, Iowa State University. 23.Management of Phytopthora root rot in soybeans............................................................... 115 Anne Dorrance, Plant Pathology, The Ohio State University. 24.A review of the 2008 growing season from a pathologist’s perspective................................ 123 Alison Robertson, Plant Pathology, Iowa State University. 25.Increasing the odds of a profitable yield response to foliar fungicide application on corn... 131 Alison Robertson and Daren Mueller, Plant Pathology, Iowa State University. 26.Use of fungicides to control soybean foliar diseases: A four-year summary......................... 139 X. B. Yang, Plant Pathology, Iowa State University. 27.Importance of glyphosate resistant Palmer amaranth and potential implications on common waterhemp...................................................................................................... 143 Jason Norsworthy, Crop, Soil and Environmental Sciences, University of Arkansas. 28.Is there a reason to consider stewardship or is killing weeds good enough?........................ 149 Mike Owen, Agronomy, Iowa State University. Matt Helmers, Agricultural and Biosystems Engineering, Iowa State University. Mark Hanna, Agriculture and Biosystems Engineering, Iowa State University. Mahdi Al-Kaisi, Agronomy, Iowa State University. Joost Korpel and Cam Conrad, Iowa Department of Natural Resources; Kristine Schaefer and Rich Pope, Pest Management and Environment Program, Iowa State University. d Eileen Cullen, Entomology, University of Wisconsin-Madison. 41.Soils 101: How to apply the information in the Clay county soil survey for northwest Iowa farmers and ag-professionals...................................................................... 295 Paul Kassel, Extension Field Agronomist, Iowa State University. 6 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 7 Speaker contact information David Asbridge Senior Economist Doane Advisory Services 77 Westport Plaza, Suite 250 St Louis, MO 63146 314/372-3575 dasbridge@doane.com Connie Hardy Extension Program Specialist, Value Added Agriculture Iowa State University 1111 NSRIC Ames, IA 50011-3310 515/294-8519 chardy@iastate.edu Kathleen Delate Associate Professor, Horticulture Iowa State University 106 Horticulture Ames, IA 50011-1100 515/294-7069 kdelate@iastate.edu Chad Hart Assistant Professor, Economics Iowa State University 468E Heady Hall Ames, IA 50011-1070 515/294-9911 chart@iastate.edu Anne Dorrance OARDC-Plant Pathology The Ohio State University Selby Hall 1680 Madison Ave Wooster, OH 44691 330/202-3560 dorrance.1@osu.edu Emily Heaton Assistant Professor, Agronomy Iowa State University 1403 Agronomy Hall Ames, IA 50011-1010 515/294-1310 heaton@iastate.edu ra Steve Barnhart Professor, Agronomy Iowa State University 2104 Agronomy Hall Ames, IA 50011-1010 515/294-1923 sbarnhar@iastate.edu Matthew Darr Assistant Professor, Agricultural and Biosystems Engineering Iowa State University 202 Davidson Hall Ames, IA 50011-3080 515/294-8545 darr@iastate.edu ft Mahdi Al-Kaisi Associate Professor, Agronomy Iowa State University 2104 Agronomy Hall Ames, IA 50011-1010 515/294-1923 malkaisi@iastate.edu Gregory Bennet Postdoc Research Associate, Agricultural and Biosystems Engineering Iowa State University 1551 Food Science Ames, IA 50011-1061 515/294-6358 gsbennet@iastate.edu d d ra ft Lori Abendroth Agronomy Specialist, Agronomy Iowa State University 2104 Agronomy Hall Ames, IA 50011-1010 515/294-5692 labend@iastate.edu Allison Burgers Graduate Research Assistant, Food Science & Human Nutrition Iowa State University 1551 Food Science Ames, IA 50011-1061 515/294-3011 aburgers@iastate.edu Eileen Cullen Assistant Professor, Extension Specialist University of Wisconsin – Madison 1630 Linden Drive Madison, WI 53706 608/261-1507 cullen@entomology.wisc.edu Mike Duffy Professor, Economics Iowa State University 478E Heady Hall Ames, IA 50011-1070 515/294-6160 mduffy@iastate.edu William Edwards Professor, Economics Iowa State University 478C Heady Hall Ames, IA 50011 515/294-6161 wedwards@iastate.edu Roger W. Elmore Professor, Agronomy Iowa State University 2104 Agronomy Hall Ames, IA 50011-1010 515/294-1923 relmore@iastate.edu Mark Hanna Extension Ag Engineer, Agricultural and Biosystems Engineering Iowa State University 200B Davidson Hall Ames, IA 50011-3080 515/294-0468 hmhanna@iastate.edu Matt Helmers Assistant Professor, Agricultural and Biosystems Engineering Iowa State University 209 Davidson Hall Ames, IA 50011-3080 515/294-6717 mhelmers@iastate.edu Charles Hurburgh, Jr. Professor, Agricultural and Biosystems Engineering Iowa State University 1541 Food Science Ames, IA 50011 515/294-8629 tatry@iastate.edu Kevin Johnson Graduate Research Assistant, Entomology Iowa State University 113A Insectary Ames, IA 50011 515/294-8663 john2057@iastate.edu 8 — 2008 Integrated Crop Management Conference - Iowa State University Palle Pedersen Assistant Professor, Agronomy Iowa State University 2104 Agronomy Hall Ames, IA 50011-1010 515/294-1923 palle@iastate.edu John E. Sawyer Professor, Agronomy Iowa State University 2104 Agronomy Hall Ames, IA 50011-1010 515/294-1923 jsawyer@iastate.edu Joe Lauer Professor, Agronomy, University of Wisconsin 1575 Linden Drive-Agronomy Madison, WI 53706 608/263-7438 jglauer@facstaff.wisc.edu Richard Pope Extension Program Specialist, Entomology Iowa State University 323 Bessey Hall Ames, IA 50011-1020 515/294-5899 ropope@iastate.edu Kristine Schaefer Extension Program Specialist, Entomology Iowa State University 8 Insectory Ames, IA 50011-3140 515/294-4286 schaefer@iastate.edu Larry Purcell Professor, Chair for Soybean Research, Crop, Soil and Environmental Sciences University of Arkansas 1366 W. Altheimer Drive Fayetteville, AR 72704 479-575-3893 lpurcell@uark.edu Howard Shepherd Extension Program Specialist, Center for Crops Utilization Research Iowa State University 1569 Food Science Ames, IA 50011-1061 515/294-3137 howard@iastate.edu Gyles Randall Professor, Southern Research and Outreach University of Minnesota 35838 120th St Waseca, MN 56093 507-835-3620 grandall@umn.edu S. Elwynn Taylor Professor, Agronomy Iowa State University 2104 Agronomy Hall Ames, IA 50011-1010 515/294-1923 setaylor@iastate.edu ra Antonio Mallarino Professor, Agronomy Iowa State University 3216 Agronomy Hall Ames, IA 50011-1010 515/294-6200 apmallar@iastate.edu d Daren Mueller Extension Program Specialist, Plant Pathology Iowa State University 351 Bessey Hall Ames, IA 50011 515/460-8000 dsmuelle@iastate.edu Jason Norsworthy Associate Professor Dept of Crop, Soil and Environmental Sciences University of Arkansas 1366 W. Altheimer Drive Fayetteville, AR 72704 479/575-8740 jnorswor@uark.edu Matt O’Neal Assistant Professor, Entomology Iowa State University 117 Insectary Ames, IA 50011 515/294-8622 oneal@iastate.edu Marlin Rice Professor, Entomology Iowa State University 109 Insectary Ames, IA 50011-3140 515/294-1101 merice@iastate.edu Greg Thessen Director, Iowa Field Office National Ag Statistics Service 833 Federal Building 210 Walnut Street Des Moines, IA 50309 515/284-4340 greg_thessen@nass.usda.gov Angela Rieck-Hinz Extension Program Specialist, Agronomy Iowa State University 2104 Agronomy Hall Ames, IA 50011-1010 515-294-9590 amrieck@iastate.edu X.B. Yang Professor, Plant Pathology Iowa State University 319 Bessey Hall Ames, IA 50011-1020 515/294-8826 xbyang@iastate.edu Elwynn Taylor, Professor, Agronomy, Iowa State University The first 9 years of the “2000s” have delivered dry streams that had not been dry in 100 years and floods that set new record high crests. The average number of stormy days consistently climbed. Corn yields climbed and the annual deviation from the trend yield diminished, yet history says “this is the 3rd time yields have been consistent over a run of a decade of more.” The climate has always changed and always will change. Historically the roots of the National Weather Service began with the initial mission of “keeping a diary of the weather,” and establishing “any material change in the climate…and if so…its dependence upon cultivation of the soil, density of population, etc.” With the original mission again at the forefront we find that 191 years of experience has not answered the questions in full, but has given a sense of the climate variability. Dealing with the risks imposed by long-term and decade scale variability has become increasingly important to producers and to consumers as well. ft Randy Killorn Professor, Agronomy Iowa State University 3208 Agronomy Hall Ames, IA 50011-1010 515/294-3433 rkillorn@iastate.edu Iowa climate: a century of change Climate is the basis of relatively consistent Midwest corn yields during the past 11 years. Records indicate that such conditions are not unique. Climate exhibits decade scale variability as well as long-term change. Dealing with the associated risks to agricultural production has become increasingly important to producers and consumers as well. Precipitation, summer heat, and frost risk seem to cycle in a 50-year to 60-year period. Some researchers involved in physical description of climate changes (climate modelers) have surmised that man-made conditions have reached the point of dominance in our climate, others contend that the global scale impact of cyclic marine events (El Nino, Pacific Decadal Oscillation, North Atlantic Oscillation, etc.) are not likely to have their cycles broken quite so suddenly as this. The latter group cautions us not to assume the current run of conditions will persist and not to be surprised is the global temperature diminishes over an interval of 20 to 30 years while the globe continues to warm (remember your High School teacher telling you that heat and temperature are not the same thing and can even move in opposite directions?). Personally I fall into the latter group (it appears that most climatologists with more than 40 years in the profession do, perhaps it is just a function of age). At least until proven wrong, I think it a mistake to assume that the consistent Midwest crop yield trend will continue indefinitely. ra Alison Robertson Assistant Professor, Plant Pathology Iowa State University 317 Bessey Hall Ames, IA 50011-1020 515/294-6708 alisonr@iastate.edu d Micheal D. K. Owen Professor, Agronomy Iowa State University 2104 Agronomy Hall Ames, IA 50011-1010 515/294-1923 mdowen@iastate.edu ft Paul Kassel Extension Field Agronomist Clay County Extension 110 West 4th Street, Ste 100 Spencer, IA 51301-3858 712/262-2264 kassel@iastate.edu 2008 Integrated Crop Management Conference - Iowa State University — 9 Floods Observations to solve the confusion as to the nature of climate change and to identify the extent of natural or human influence are about to enter their 3rd century. It was 1818 when the US Government established the Climate Observation Network that in time became the National Weather Service. Each military instillation was required to maintain a standardized Diary of Climate Observations. The responsibility fell to the instillation physician, apparently it was important to have a person who could write and had a thermometer. In time the responsibility was transferred to the Signal Officer and ultimately the weather service became the responsibility of the Department of Commerce. Iowa has several climate observation sites with records extending some years before 1900 that have rather complete records up to the present. A count of the annual number of days reported 10 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 11 d The annual amount of precipitation varies from year to year and intervals of somewhat moist or somewhat dry over a period 20 or so years are apparent. The “cyclic” dry or wet series of years allows us to compute the risk of both drought and flood for some years in advance. Climatologists speak of deviation from normal temperature or precipitation. The “normal” is defined as the average of 30 years of record. The current normal is established by the 1971-2000 period. The normal interval was established in an effort to identify long-term climate change with minimal impact from multi-year cyclic weather trends. Overall Iowa (together with most Midwest states) has experienced a long-term increase in annual precipitation. The increase for central Iowa was near 10% over the latter half of the past century. A relatively small increase of precipitation can result in a large impact on stream flow. ft ra Figure 1. Annual days with measurable precipitation at 35 climate recording sites across Iowa from 1893-2007. The data indicate the number of days when rain was reported at the climate stations. The increase over time is influenced by both the number of storms and the area covered by storms as each would influence the chance of rain at the measurement point. Data and graphic provided by www.mesonet.agron.iastate.edu , Daryl Herzmann. Figure 2. Annual precipitation at Ames, Iowa 1893-2007. The increase in annual precipitation is consistent with observations throughout Iowa. Relocation of the observing site and changes in the type of rain gauge as well as land use changes near the site impact the long-term record. Single site records (such as this) are compared with near-by stations to determine the validity of apparent changes in climate. Precipitation in excess of evaporation from land, plants, and water bodies is either retained in the soils, ponds, and subsurface features of the landscape or appears as run-off in rivers and streams. Also there is some consumption of water by other, human, activities. Vegetation, including agricultural crops, utilizes about 25 inches of water per year, if sufficient water is available in a timely manner. Naturally intense precipitation events result in almost immediate run off, however, light to moderate events may infiltrate the soil and run off is limited to the amount in excess of the capacity of the landscape retain moisture. If precipitation does not exceed the potential utilization by the vegetation the streams will soon diminish and cease to flow altogether. Imagine that 25 inches of precipitation fell over the course of the year and the streams were dry although the crops did well, such as was the case in much of Iowa during 2002. If 26 inches of precipitation fell the streams would have a trickle. Add another inch, 27 inches, and double the stream flow. A year with 29 inches of moisture would double the flow again. At 33 inches we have doubled the stream flow one too many and flooding becomes likely. Historical flow of Iowa rivers has responded to the increased trend in precipitation in this very way, the average annual flow of most if not all Iowa rivers has doubled during the past 50 years. d ra ft to have precipitation from the 1890s up to now, for the same Iowa sites, showed that Iowa climate stations experienced about 60 days with precipitation during the early 1890s and 120 days with measurable precipitation by the year 2000. The increased rain days appears to be somewhat cyclic over the history indicating possible changes on the order of 20 years and a long term climate change as well. 12 — 2008 Integrated Crop Management Conference - Iowa State University Accordingly the rivers are at levels of increased flood probability some six times as often as under the previous regime of precipitation. When the rivers are in flood prone condition six times as often we might expect 100-year flood levels to return at six times the frequency as well. The approximate return period of the 100-year flood level thus becomes 17 years. 2008 Integrated Crop Management Conference - Iowa State University — 13 the incidence of flooding will continue to increase and if long-term climate “cycling” still has an influence some reversion to conditions more like the 1960s is possible during the coming 30 year interval. The latter condition may reduce flooding risk while global scale warming may cause the flood risk to continue to increase. Rough computations for a global scale warming of 5 degrees anticipate 100-year flood levels at a risk level of one in five. The reality of a 17 year return period of severe flooding makes a significant impact on flood risk planning; should a building be repaired after receiving flood damage or is it more advantageous to relocate the facility? Climate is in a continuous state of change. Historically, annual precipitation waxes and wanes over an approximately 60-year period. If the Midwest has entered a 30-year drying phase the probability of serious flooding will diminish somewhat over a period of a few years. Most climate models currently assume that 60-year type cycles have been broken and global scale trends will be consistent with increasing “green house” forcing of the climate. Major flooding should be expected to be increasingly common. Global Circulation Models have greatly improved over the past 20 years but the scientists developing the models seem to still be finding ample challenge for their intellectual abilities. Old school climatologists would be surprised if long-term trends stabilize. This means that if “global heating” is in control ft The average date of freezing does serve to give guidelines as most producers do not want a 50/50 of a killing freeze. Although central Iowa may be frost free after April 10th (1987, 2006), occasionally the last freeze has been as late as May 13th (1997). Although spring in recent years is some 7 days earlier than in the 1950s there has been little change in the risk of spring freeze. Basically a freeze in central Iowa is rare after May 10th. Most are willing to take a bit of a chance on the 1 in 5 risk of frost damage to corn that has emerged by May 5th since freezing of the leaves of the very small plant is normally not a major setback to the corn as the growing point of the plant is protected by a recessed position in the plant. ra d Figure 3. Average annual flow. The average annual flow in the Turkey river of NE Iowa is typical of flow pattern noted for rivers throughout Iowa. When the average flow exceeds 1400 units the river, somewhat arbitrarily, becomes “flood prone.” The increased flow of the past 50 years has resulted in a six-fold increase in the number of flood prone years (and likely in the actual number of floods as well). Data from; http://nwis.waterdata.usgs.gov/ia/ nwis/annual The freeze sets the limit of the Midwest growing season. Generally we consider spring crops to be sensitive to freezing temperature although the leaves and flowers of most plants are not damaged until the temperature is somewhat below 32F. Because it is often a few degrees colder near the ground than it is 4 or 5 feet above the ground where the temperature is typically measured the assumption that 32F is the “killing” temperature is appropriate in spring. The killing freeze for Corn and Soy in the fall is considered to be 28F. The same rules apply as in the spring but the crop is more robust and the crop canopy itself is a protection to the near-ground parts of the plants. The 56 year historical average last 32F temperature in the spring is April 24th in central Iowa. The average date of the first 28F freeze of fall is October 19th. The first fall killing freeze may be well before the average date. However, seriously early fall freeze has been minimal since the early 1980s. Accordingly many farmers seem willing to take the chance of an early freeze when they consider the yield advantage of the full season crop although untimely freeze would be costly. In summary the impact of the changing climate on the frost free season is present but the impact on agriculture is not substantial to date. d ra ft Freeze Drought d The US Corn Belt has not suffered serious drought since the event of 1988. This is not to say that drought has not been a factor during subsequent years. Most crop yield models that have a record of accurate prediction are based on crop water availability. Water availability has remained the most limiting factor during the past 20 years. However, temperature considerations are a close second and in several years have been dominating (including 2008). Seven consecutive years of above trend corn yield in Iowa is unprecedented but is not totally out of character for the pattern of crop-weather response observed since corn yield records began in the 1860s. Three cycles of consistent yield separated by a multi-year interval of erratic yield have been noted. During the past season (2008) rain fall diminished across most of Iowa during July and August. Because of late planting and planting into excessively wet soils root systems did not appear to be normally vigorous. In past wet springs crops have suffer substantial yield loss during stressfully hot summer days when plants were unable to obtain sufficient moisture to satisfy atmospheric demand. During the 2008 season the temperature was not excessive during the summer (no high temperature records were set in the state of Iowa). The subsequent reduction of water demand was within the capacity of the existing root systems, resulting in yields that generally exceeded the trend. ft ra Figure 4. Length of the central Iowa growing season in days. The length of the growing season west of Ames, Iowa shortened from 1950 through 1974 and has subsequently recovered to approximately the conditions of the 1950s during the past 15 years. The pattern resembles that of the global scale change in average annual temperature. 2008 Integrated Crop Management Conference - Iowa State University — 15 Figure 5. Iowa corn yield 1945-2007. Intervals of consistent yield and of erratic yield are evident throughout the recorded history of corn production in the US. Tree ring data indicate that serious drought in the central and eastern US recurs at approximate intervals of 19 years. Over the past 800 years (in Virginia) the longest interval between serious droughts is 23 years. If the Corn Belt passes 2011 without experiencing serious drought an apparent new record for the Midwest and eastern US will be established. We have no observed insistences of wide-spread drought in the Corn Belt during El Nino events. However, drought risk is greater than the average during La Nina years. The La Nina in place in September and October 2008 may or may not persist to increase drought risk during the 2009 season. Additionally the La Nina tends to be associated with volatile winter conditions. The redevelopment of La Nina during the fall of 2008 opens the possibility of a winter not unlike the 2007-8 winter season in the Midwest. d ra ft 14 — 2008 Integrated Crop Management Conference - Iowa State University Growing degree days The growing degree day computation is intended to sum the aspects of temperature that most influence plant development. The unit is defined by the low temperature when plants cease to grow and the high temperature where stress usually initiates (50F and 86F for corn). There is no apparent change in the monthly accumulation of growing degree days from 1893 until the 16 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 17 present for the summer months at Ames, IA. However, no other locations have been analyzed. Resources needed for record-breaking soybean yields Summary Larry C. Purcell, Professor, Crop, Soil and Environmental Sciences, University of Arkansas In 2006, the soybean industry was astounded when Kip Cullers, a farmer in southwest Missouri reported yields of 139 bushels per acre in the Missouri Soybean Association yield contest. These amazing yields were shattered in 2007 when Mr. Cullers reported yields of 155 bushels per acre. Previous to Mr. Cullers’ reports, the record yield was 118 bushels per acre set in small-plot research by Dr. Roy Flannery in 1983 at Rutger’s University in New Jersey. ft The unprecedented yields from Mr. Cullers’ farm have been met with an equal mix of excitement and skepticism. Crop scientists have generally concluded that the theoretical yield potential of soybean in the absence of drought stress was approximately 110 to 120 bushels per acre (Sinclair, 2004; Specht et al., 1999). Theoretical yield potentials for soybean are based upon relationships of: • the amount of crop mass that can be accumulated for each unit of light energy that the crop intercepts, • the total amount of light that the crop can intercept during a growing season, ra • how long during seed development the crop can maintain these high rates of crop growth, • the availability of nutrients, particularly nitrogen, to meet demands of growing proteinrich seeds, and • the amount of seed that the crop produces from the total above-ground plant weight (the harvest index, HI) During the 2008 growing season, Mr. Cullers allowed me access to his contest soybean field. Although yields for the 2008 season from Mr. Cullers are not available as I write this report, I can describe my observations and measurements made during the season. I established small plots in his field where three varieties that ranged from a maturity group 4.7 to a 5.9. Measurements I made were aimed at documenting the amount of light energy intercepted by the crop, how efficiently that light energy was used for crop growth (weight), the rate and duration of seed growth during the season, and changes in leaf nitrogen concentration that occurred during seed growth. d d ra ft It will not be a surprise if the winter harshness this year is similar to the 2007-8 winter. Also, moist conditions at planting would be expected but not to the extent of the record flooding that occurred during the past spring. Growing Degree Days lagged seriously in many areas during 2008. This delayed crop development but after flowering served to allow extended calendar days for crops to gain dry weight. We cannot expect a repeat of this condition. It is not known if the La Nina condition that established in late summer and fall will persist into the 2009 growing season. However, if it does, it will increase the risk of adversely hot weather during the summer. It would be nice to have another year of national corn yields that exceed the trend, but history does not give us reason to think the weather will cooperate so many consecutive years. Mr. Cullers’ crop was completely canopied 40 days after emergence, and efficiency of light energy use for crop growth was high but similar to what others have reported. Once the crop began flowering, it was irrigated (~0.25 inch) most days when temperature was above 95 F. Leaf samples taken beginning at full bloom and extending throughout seed fill showed a gradual decrease in shoot nitrogen concentration (Figure 1). Of particular note was that at physiological maturity (R7), there was a near full canopy of green leaves (Figure 2) that had nitrogen concentrations of around 3% (Figure 1). 18 — 2008 Integrated Crop Management Conference - Iowa State University Measurements made during 2008 were then used to predict theoretical yield potential for the 2007 and 2008 seasons using a crop growth model (Sinclair et al., 2003). The model uses daily measurements of temperature and light energy along with values for how efficiently light is used by the crop for growth and how quickly seeds grow. d References Sinclair, T.R. 2004. Improved carbon and nitrogen assimilation for increased yields. p. 537-568. In H.R. Boerma and J.E. Specht (ed.) Soybeans: Improvement, production and uses 3rd ed. ASA, CSSA, and SSSA. Madison, WI. Sinclair, T.R., J.R. Farias, N. Neumaier, and A.L. Nepomuceno. 2003. Modeling nitrogen accumulation and use by soybean. Field Crops Res. 81:149-158. Specht, J.E., D.J. Hume, and S.V. Kumudini. 1999. Soybean yield potential - A genetic and physiological perspective. Crop Sci. 39:1560-1570. 94Y70 95Y90 94M80 3 2 1 0 -60 -40 ft ra If the extraordinary yields from Mr. Cullers’ are due to increased nitrogen availability, the question becomes ‘How is enough nitrogen applied or fixed by soybean to prevent leaves from exporting their nitrogen to seeds?’ Mr. Cullers routinely applies chicken litter to his soybean fields, and 3 tons per acre of litter would supply about 180 pounds of N per acre. Mr. Cullers also uses his center pivot as a fertigation system, and the frequent irrigations during the season provide an opportunity to apply large amounts of nitrogen through many applications. Finally, Mr. Cullers’ soybean plants are well nodulated and are apparently fixing nitrogen. A combination of these factors may provide sufficient nitrogen for the crop to obtain these extraordinary yields. 4 -20 0 20 40 Days from beginning beginning seed fill 60 Figure 1. Leaf nitrogen concentration versus days from the beginning of linear seed fill. Data were from three varieties in 2008 from Kip Cullers’ contest field. Arrows indicate that plants were at, or past, physiological maturity (R7) when leaf samples were taken. ra When the model was ‘reprogrammed’ so that the crop had plentiful nitrogen throughout the season, predicted yields ranged from 134 to 160 bushels per acre. This range of yields is similar to those reported from Mr. Cullers’ contest fields. 5 d ft A major assumption of the growth model is that the amount of nitrogen that the crop can fix from the atmosphere plus the amount of nitrogen that the crop can take up from the soil is insufficient to meet the amount of nitrogen that the seed accumulates. In the model, this causes the leaves to export nitrogen to the seed, and the decrease in leaf nitrogen results in decreased crop growth and early senescence. This assumption, however, does not agree with the measurements of leaf nitrogen as the crop reaches R7 (Figure 1) or the canopy of green leaves at maturity (Figures 2 and 3). 6 Leaf N conc. (mg/100 g) The predicted yields from the growth model were between 80 and 90 bushels per acre. Although most farmers would be pleased to have yields in this range (and some do), these yields are a far cry from the yields reported in Mr. Cullers’ contest fields. 2008 Integrated Crop Management Conference - Iowa State University — 19 Figure 2. Photograph from Kip Cullers’ contest field in 2008. The photograph was taken as the crop approached physiological maturity. Note the large number of green leaves and pods approaching mature color. 20 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 21 No-tillage soybean production in Iowa Palle Pedersen, Assistant Professor, Agronomy, Iowa State University ft The adoption rate of no-tillage practices in the northern Corn Belt has been slow compared to other parts of the World. Lack of site specific knowledge of the no-tillage system has most likely been the main limitation to use in corn and soybean production. That has contributed to grower dissatisfaction mainly because of the difficulties in dealing with residue after the previous corn crop. These conditions not only result in slower emergence and growth until R2, but also may affect the stand because of poor planter performance when planting into large amounts of residue. Equipment manufacturers, however, have addressed this problem by developing new residue attachments. ra d Figure 3. Photograph from Kip Cullers’ 2007 crop. At this time, the crop was past physiological maturity. Note that all pods are mature color and that there is a near full canopy of green leaves. No-tillage has been used since ancient times by indigenous cultures and is defined as planting of crops in previously unprepared soil by opening a narrow slot, trench or band only of sufficient width and depth to obtain proper seed coverage. Until the early 1970s, tillage for corn and soybean production was mostly related to managing weeds and for seedbed preparation. Introduction of new herbicides and improved tillage and planting equipment resulted in a shift toward reduced tillage systems throughout the 1980s and 1990s. These systems require fewer, more timely passes through the field and left more crop residue on the soil surface, thus conserving fuel and reducing the potential for soil erosion. Recent environmental concerns have expanded beyond soil erosion to controlling loss of nutrients and pesticides. The adoption rate will increase in the future because of the high energy cost and the potential that farmers can sell their carbon credits from carbon sequestration to companies and even countries. No agronomic recommendations exist in Iowa for the growers that want to adopt no-tillage soybean production. A large project was funded through NCSRP from 1994-1996 across the region but nothing was published out of the Iowa data set. Many studies have been conducted since then in Iowa and neighboring states looking at tillage comparison. Despite this, no recommendation exists on how to work within the no-tillage system, minimize the risk with a no-tillage system compared to a tilled system, and how it deviates from current recommendations. For that reason a large project funded by the checkoff and the Iowa Soybean Association was initiated at 6 locations across Iowa (Figure 1). d ra ft During the 2005 growing season 63 million acres in the United States were planted using notillage production practices. Total soybean acres in Iowa in 2007 were 9.4 million and it is estimated that only about 30% of those acres were planted using no-tillage practices. The project will be conducted from 2007-2009. The overall goal of this research project is to develop management recommendations when producing soybean under no-tillage conditions under various soil types in Iowa. 22 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 23 The specific objectives are to: 1. Determine soybean growth, development and yield potential in a no-tillage production system 2. Determine optimum recommendations for soybean in a no-tillage production system (planting date, plant population, seed treatment, inoculants, row spacing) across Iowa 3. Evaluate the importance of variety selection related to soil-borne pathogens (SCN, SDS, Phytophthora resistance in a no-tillage production system, but also varieties like lowlinolenic varieties) ft 4. Determine the economic advantages or disadvantages using no-tillage production practices across Iowa Calumet ft 5. Increase awareness in Iowa on the use of no-tillage production practices Humboldt d Lenox Oskaloosa Figure. 1. The six no-tillage locations in Iowa with two locations in southern Iowa, two locations in central Iowa, and two locations in northern Iowa. Of the six locations, two locations are within the Des Moines Lobe. ra Nevada Figure 2. One of four replications at the Oskaloosa location in 2008. Strips of conventional tillage (chiseled in the fall and cultivated in the spring) are replicated and randomized with no-tillage strips. There are a total of seven different experiments to address the specific objectives. In this presentation, data from the 2007 and 2008 growing season will be presented and conclusions will be drawn based on the first two of this three year project. d ra Waterloo Acknowledgements The author would like to thank the Iowa Soybean Association for financial support of these projects and Jason De Bruin, Joseph Osenga, Alecia Kiszonas, Brent Pacha, Catherine Swoboda, Tim Berkland, and Jess Calvin for their technical assistance. 24 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 25 For crops … its rotation, rotation, rotation! The sustainability of the corn-soybean rotation Joe Lauer, Professor, Agronomy, University of Wisconsin ra ft Sustainable agriculture is a practice that over the long term enhances environmental quality and the resource base on which agriculture depends, provides for basic human food and fiber needs, is economically viable, and improves the quality of life for farmers and society (White et al., 1994). Crop rotation is a universal management practice that has been recognized and exploited for centuries and is a proven process that increases crop yields. Many reports involving tillage type, N fertilizer rate, and inclusion of a legume show yield benefit of 4 to 22% for rotated corn over continuous corn (Raimbault and Vyn, 1991; Peterson and Varvel, 1989b; Katsvairo and Cox, 2000a; b). The key benefits of including a forage or pasture crop consist of increasing soil N levels increase carbon retention in the surface horizon and a more even distribution of labor needs and risk due to climate or market conditions than those involving only grain or fiber crops (Peterson and Varvel, 1989a; Raimbault and Vyn, 199; Magdoff and van Es, 2000). Extended rotations involving forage crops may be more sustainable than current short-term agricultural practices (Randall, 2003). In the Midwestern U.S., a biennial rotation of corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] produces significant increases in the yields of both crops. Despite these benefits, the infrastructure developed and devoted to corn and soybean has resulted in a 500% increase in harvested area and 800% increase in soybean production between 1950 and 2003 (USDA-NASS, 2006). The dominant agricultural land use throughout the northern Corn-Soybean Belt became a 2-yr corn and soybean rotation during the last half of the 20th century. During that same period, oat production declined 90%, and although hay production increased because of better yields, the land area devoted to it decreased more than 15% (Karlen et al., 2006). This occurred for several reasons including simplicity and similar equipment requirements as farm size increased, commodity programs that emphasized short-term profit, public and private research and development efforts devoted to genetic improvement of corn and soybean, and increased food and industrial uses for both corn and soybean oils and various by-products (Karlen, 2004). It also coincided with major changes in the livestock industry that decreased demand for oat and alfalfa. d d ra ft Introduction The mechanism for the rotation effect is unknown. One hypothesis is that one factor causes the effect. Another hypothesis is that multiple factors cause the effect and risk of expression depends upon the environment. Research evidence began mounting in the 1970’s, which indicated that in spite of all the management inputs a farmer might impose, there was still a yield advantage to be obtained from rotations. The objective of this paper is: 1) to describe the principles of rotation, and 2) to determine the long-term effect of crop rotation and applied N on first phase corn grain yield in corn-soybean rotations and selected extended rotations. 26 — 2008 Integrated Crop Management Conference - Iowa State University Arlington experiment ra Table 2. Crop rotations and nitrogen rates at Lancaster, Wisconsin used to evaluate the influence of crop rotation and nitrogen on the rotation effect of first year corn.† Table 1. Rotation sequence for corn (C) and soybean (S) in the Arlington experiment begun in 1983 (Year 1). 1966-1976 Year Crop sequence 1 2 3 4 5 6 7 8 9 10 1 C C S S S S S C C C 2 C C C S S S S S C C 3 C C C C S S S S S C 4 C C C C C S S S S S 5 S C C C C C S S S S 6 S S C C C C C S S S 7 S S S C C C C C S S 8 S S S S C C C C C S 9 S S S S S C C C C C 10 C S S S S S C C C C 11 C C C C C C C C C C 12 S C S C S C S C S C 13 C S C S C S C S C S 14 S S S S S S S S S S d To accommodate all possible phases of the rotations and four fertilizer treatments, 168 plots (6.1 by 9.1 m) were established in 1966 in a randomized complete block in a split-plot design with two replications of 21 treatments to test the rotation effect by having each phase of every rotation represented each year. Thus, for continuous corn (CC), there were one plot within each statistical block, and for corn-soybean (CS) there was one corn plot and one soybean plot within each block. The crop sequence plots were split to accommodate four N rate treatments. From 1967 to 1976, N rates were 0, 75, 150, and 300 lb N/A, but since 1977, the annual rates have been 0, 50, 100, and 200 lb N/A for corn only (Table 2). N fertilizer treatments were applied in spring as ammonium nitrate (NH4NO3). Rotation treatments have changed over time (Table 1). Tillage has varied over time. Lancaster experiment A long-term crop rotation study located in southwestern Wisconsin at the University of Wisconsin Agricultural Research Station near Lancaster, WI (42°51’ N, 90°43’ W)] was originally established to evaluate crop rotation and N fertilization rate effects on crop yield and soil N mineralization, retention, and availability (Vanotti and Bundy, 1994, 1995). The study was 1977-1986 1987-2004 CC CC CC CSCOaA CSCOaA CSCOaA CCCOaA CCCAA CCCAA CCOaAA CCOaAA CCOaAA COaAAA CCAA CA COaAAA CCAA CS COaAAA AA Crop Rotation Treatments d ra ft A long-term crop rotation study located in south central Wisconsin at the University of Wisconsin Agricultural Research Station near Arlington, WI (43°18’ N, 89°20’ W) on a Plano silt loam soil (fine-silty, mixed, mesic, Typic Argiudoll) was originally established to evaluate crop rotation, tillage and management effects on crop yield. The experimental design is a randomized complete block in a split-split plot arrangement with four replications. Main plots are conventional tillage and no-tillage systems that were established in 1986. Conventional tillage is accomplished by a chisel plow in the fall and two passes of field cultivation in the spring before planting. For no-tillage, crops are planted directly into the undisturbed residue of the previous crop. The subplots consisted of 14 rotation sequences involving corn and soybean, which had been established in 1983 on land previously planted to corn (Table 1). The sequences allowed comparisons to be made of (i) first-year corn and soybean (after a minimum of five consecutive years of the other crop); (ii) corn and soybean alternated annually with the other crop; and (iii) second, third, fourth, and fifth or more years of continuous corn and soybean (Table 1). The split-split-plots have been various management treatments over time. Plot size of the subsubplot experimental units was 3.0 by 9.4 m. located on Rozetta (fine-silty, mixed, superactive, mesic Typic Hapludalfs) soil, which consists of very deep well-drained soils formed in loess on uplands (USDA-SCS, 1961). Permeability is moderate, and slopes range from 0 to 25%. Mean annual temperature and precipitation are 51 °F and 36 inches, respectively. The site is located in the driftless area of Major Land Resource Area (MLRA) 105 found in southwest Wisconsin, southeast Minnesota, northeast Iowa, and northwest Illinois (USDA-SCS, 1981). ft Materials and methods 2008 Integrated Crop Management Conference - Iowa State University — 27 Nitrogen Treatments (lb N / A) † 0 0 0 75 50 50 150 100 100 300 200 200 C, corn; S, soybean; Oa, oat with alfalfa seeding; A, alfalfa. The Lancaster cropping systems study is comprised of multiple crop rotations that take varying amounts of time to complete a rotation sequence. For example, CC takes 1 yr , CS takes 2 years, and CSCOaA takes 5 yr s (Table 2). However, the traditional analysis using years can be expanded to analyze both spatial and temporal trends based on the average yields produced in the period it took to accomplish the cycle. By doing this, we can see how the rotations preformed when they returned to the same piece of ground allowing data analysis across both time and C= Corn, S= Soybean, Number = consecutive year of corn Results and discussion Arlington experiments – The principle of crop rotation ft The rotation effect lasts two years increasing corn grain yield 10 to 19% for 1C following five years of soybean and 0 to 7% for 2C (Figure 1). The rotation effect lasts two years increasing soybean grain yield 10 to 20% for 1S following five years of corn production and 8% for 2S (Figure 2). 162 160 140 18% A 19% A 7% B 155 3% CD 156 155 120 3% 3% C CD D 1C 2C 3C 4C 5C CC Cropping Sequence C= Corn, S= Soybean, Number = consecutive year of corn d Figure 1. Corn yield response following five years of soybean at Arlington, WI. Grain Yield (bushels/acre) 70 60 54 59 1987-2006 53 50 50 50 48 49 2% C 1% CD -1% D CD 4S 5S CC 40 1987-2006 53 50 50 50 48 49 2% C 1% CD -1% D CD 40 30 20 10 10% B 20% A CS 1S 0 8% B 2S 3S 4S 5S CC Cropping Sequence C= Corn, S= Soybean, Number = consecutive year of soybean 151 100 CS 54 59 Figure 2. Soybean yield response following five years of corn at Arlington, WI. Lancaster experiments – The sustainability of crop rotations ra 179 60 Regression slopes of each phase of corn within each rotation sequence were evaluated to determine the long-term effects of various crop rotations and different N fertilization rates on grain yield. We compared each regression slope to zero to determine if over time the rotation treatments were improving or deteriorating, and to each other to determine if the relative slopes of each treatment are converging or diverging (Figure 3). d 178 ra Grain Yield (bushels/acre) 180 1987-2006 70 Grain Yield (bushels/acre) space. Hence, we analyzed the data in groups of either 2- or 5-yr s depending on the length of the rotation cycle using CC as our control. 200 2008 Integrated Crop Management Conference - Iowa State University — 29 ft 28 — 2008 Integrated Crop Management Conference - Iowa State University 30 20 10 10% B 20% A CS 1S 8% B 0 2S 3S Cropping Sequence C= Corn, S= Soybean, Number = consecutive year of soybean Figure. 3. How can you tell if a cropping system is changing? Theoretical changes over time in cropping systems relative to the control cropping system. 30 — 2008 Integrated Crop Management Conference - Iowa State University ft Rotating corn significantly improved corn grain yield over time for the first phase of corn when compared to CC (Table 3). For the 0 lb N/A treatment, grain yield for CCCAA, CCOaAA, and CSCOaA rotations improved 1.2 to 1.3 bu /A yr , respectively. In the 50 lb N/A treatment where N was applied but limiting, CCCAA, CCOaAA, and CSCOaA improved grain yield by 1.1 to 1.2 bu/A yr , respectively. For the 100 lb N/A treatment, CCCAA, CCOaAA, and CSCOaA improved grain yield 1.4 to 1.5 bu/A yr , respectively. Overall, within a diversified crop rotation and with adequate N (200 lb N/A), corn yields improved by 1.6 bu/A yr or 1.4 % per year, which is similar to the national average (USDA-NASS, 2006). ra There was no difference in slope for the first phase of corn when comparing the 2, 3, and 4-crop rotation sequences at each N rate (Table 3). These results suggest as long as the previous crop is not corn, each rotation sequence in this study is equally effective in breaking the yield depression caused by monoculture. Table 3. Corn grain yield rate of change for the first phase of corn (bu /A yr ) of 5-yr rotations in various N rate (lb N/A) treatments at Lancaster, WI from 1970 to 2004 (seven 5-yr cycles). Rotation 0 lb N/A 50 100 200 lb N / A Rotation NS † CCCAA 1.2** 1.1** 1.4** 1.6** CCOaAA 1.3** 1.2** 1.5** 1.6*** 1.4*** 1.6*** CSCOaA 1.2** 1.1** †, *, **, *** Significant at the 0.10, 0.05, 0.01, and 0.001 levels, respectively 2-yr Rotations (1989 – 2004) Through 16 years (eight 2-yr cycles) CC grain yield at all N-rate levels was not affected over time and thus did not improve or deteriorate (Table 4). Corn grain yield in the CS rotation at 0 lb N/A decreased by 3 bu/A yr . A similar trend was found for the CA rotation. Rotating corn with a legume improves corn grain yield over time only when additional N is added to the system. 100 200 CC NS NS NS NS CA † NS NS NS NS NS CS -3.0* NS †, *, **, *** Significant at the 0.10, 0.05, 0.01, and 0.001 levels, respectively 5- vs. 2-yr rotations (1990 – 2004) A comparison was made of both the 5-yr rotations with the 2-yr rotations from 1990 to 2004, on a 5 yr cycle. The slopes of the rotations at each of the N rates are not significantly different from a zero slope, except for the decreasing slopes of CA and CS rotations at 0 lb N/A (Table 5). Since 1990, in the 0 lb N/A treatment, grain yields have actually declined by 2.5 and 2.8 bu/A yr for the CA and CS rotations, respectively. For the 50 lb N/A treatment, the CS rotation decrease grain yields over time by 2.5 and 2.7 bu/A yr when compared to the CCCAA and CCOaAA rotations, respectively (Table 6). For the 100 lb N/A treatment, the CC rotation decrease grain yields over time by 2.5 bu/A yr when compared to the CCCAA rotation. Since 1990 in the 200 lb N/A treatment, the CC rotation decreased grain yields over time by 2.6 and 2.5 bu/A yr when compared to the CCCAA and CSCOaA rotations, respectively. Table 5. Corn grain yield rate of change for corn (bu/A yr ) of 5-yr and 2-yr rotations in various N rate (lb N/A) treatments at Lancaster, WI from 1990 to 2004 (three 5-yr cycles). Rotation 0 lb N/A 50 100 200 --------------- bu /A yr --------------- CC NS NS NS NS CA -2.5* NS NS NS CS -2.8* † NS NS CCCAA NS NS NS NS CCOaAA NS NS NS NS NS NS d NS d NS 50 bu/A yr ---------------- bu /A yr ---------------- CC 0 ft Corn grain yields increased from 1.1 to 1.6 bu /A yr with increasing N rates (0 and 200 lb N/A, respectively) for corn that was rotated (Table 3). Relative yield trends for continuous corn did not improve over time no matter the N rate. Thus, there was no yield gain with adopting improved hybrids during the 35-yr of this study. This suggests two things, either hybrids have not improved since 1970, or that improved hybrids have kept continuous corn yield trends from declining over time. Currently, with the rapid turnover of hybrids there is no way to answer this question. Table 4. Corn grain yield rate of change for corn (bu/A yr ) of 2-yr rotations in various N rate (lb N/A) treatments at Lancaster, WI from 1989 to 2004 (eight 2-yr cycles). ra 5-yr rotations – First corn phase (1970 – 2004) 2008 Integrated Crop Management Conference - Iowa State University — 31 CSCOaA NS NS †, *, **, *** Significant at the 0.10, 0.05, 0.01, and 0.001 levels, respectively 32 — 2008 Integrated Crop Management Conference - Iowa State University 0 50 100 200 --------------- bu /A yr --------------3.8*** NS NS NS CC vs. CS 4.1*** NS NS NS CC vs. CCCAA NS NS -2.5* -2.6* CC vs. CCOaAA NS NS NS NS CC vs. CSCOaA NS NS NS -2.5* NS NS NS NS CA vs. CCCAA -3.0*** NS NS NS CA vs. CCOaAA -2.7* † NS NS -2.7* NS NS NS CS vs. CCCAA -3.3*** -2.5* NS NS CS vs. CCOaAA -3.0*** -2.7* NS NS CS vs. CSCOaA -2.9*** NS NS NS CA vs. CS ra CA vs. CSCOaA ft CC vs. CA † *, **, *** Significant at the 0.10, 0.05, 0.01, and 0.001 levels, respectively d Based on these results, time (2+ yr ) along with rotation were required between corn crops to improve corn grain yields. We agree with Randall (2003) and Karlen et al. (2006) that extended rotations involving forage crops may be more sustainable than current short-term agricultural practices. However, according to Karlen et al. (2006) without the support of federal incentive programs such as the Conservation Security Program or other public and private research and development efforts, markets and uses for forage-based products developed to promote economic and environmental sustainability, farmers will hesitate to adopt more sustainable practices. Conclusions This data shows a long-term corn grain yield advantage of extended rotations when compared to 2-yr rotations and continuous corn. Nitrogen plays a major role in maintaining and improving corn grain yields in the absence of crop rotation. The addition of N removed the corn grain yield trend differences between CC and the first phase of corn in 5-yr rotations. Alfalfa in an extended crop rotations supplied most of the N required by the first phase of corn and yield improved over time. For the second phase of corn a lower but still substantial amount of the total N requirement was supplied from the previous alfalfa crop, however, additional N was needed in order to improve corn grain yields over time. An application of 200 lb N/A was needed for continuous corn grain yield improvement over time. The net effect of legumes in improving corn grain yield trends of subsequent corn was not evident for corn that was annually rotated (CA and CS). If no N is added, CA and CS appeared to depress corn grain yields with time. A single legume crop yr was only beneficial in maintaining These results support the argument that extended rotations involving forage crops may be more sustainable than current short-term agricultural practices, because time (2+ yr) along with rotation and nitrogen were required to improve corn grain yields. However, without proper incentives like the Conservation Security Program, farmers may hesitate to adopt more sustainable practices. Some other considerations when making rotation decisions include: • If there is only a one-year break in the rotation then the second corn phase is equivalent to continuous corn. At least two break years are needed to measure a response in the second corn phase (compared to CC). ft Rotation • Adding a third crop like wheat (Triticum aestivum L.) does not increase corn grain yield, but does improve soybean grain yield. • Modern corn hybrids and management practices have the same rotation response as older hybrids and practices. Although scientists cannot yet satisfactorily explain the rotation effect, farmers can exploit it every year. The age-old practice of rotating crops, which was once considered unnecessary and perceived to be overcome with modern hybrids, has returned to today’s agriculture with proven benefits. ra lb N / A corn yields over time if nitrogen was added to the system. When all rotations were compared (1990 to 2004), corn grain yields trends of 5-yr crop rotations were significantly better where no N was added and additional N was required for the 2-yr rotations to eliminate this difference. References Karlen, D.L. 2004. Cropping systems: Rain-fed maize-soybean rotations of North America. p. 358-362. In: R.M. Goodman (ed.). Encyclopedia of plant and crop science. Marcel Dekker, Inc., New York. Karlen, D.L., E.G. Hurley, S.S. Andrews, C.A. Cambardella, D.W. Meek, M.D. Duffy, and A.P. Mallarino. 2006. Crop rotation effects on soil quality at three Northern Corn/Soybean Belt locations. Agron. J. 98:484-495. d Table 6. Corn grain yield rate of change contrasts for corn (bu/A yr ) in 5-yr (first phase) and 2-yr rotations in various N rate (lb N/A) treatments at Lancaster, WI from 1990 to 2004 (three 5-yr cycles). 2008 Integrated Crop Management Conference - Iowa State University — 33 Katsvairo, T.W., and W.J. Cox. 2000a. Economics of cropping systems featuring different rotations, tillage, and management. Agron. J. 92:485-493. Katsvairo, T.W., and W.J. Cox. 2000b. Tillage x rotation x management interactions in corn. Agron. J. 92:493-500. Magdoff, F., and H. van Es. 2000. Crop rotations. p. 99-108 In: Building soils for better crops. 2nd ed. Sustainable Agric. Publ., Univ. of Vermont, Burlington, VT. Peterson, T.A., and G.E. Varvel. 1989a. Crop yield as affected by rotation and nitrogen rate: I. Soybean. Agron. J. 81:727-731. Peterson, T.A., and G.E. Varvel. 1989b. Crop yield as affected by rotation and nitrogen rate: III. Corn. Agron. J. 81:735-738. Raimbault, B.A., and T.J. Vyn. 1991. Crop rotation and tillage effects on corn growth and soil structural stability. Agron. J. 83:979-985. 34 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 35 Randall, G.W. 2003. Present-day agriculture in southern Minnesota-is it sustainable? [Online]. Available at http://sroc.coafes.umn.edu/Soils/Recent%20Publications%20and%20 Abstracts/Present-Day%20Agriculture.pdf (verified 11 July 2006). Univ. of Minnesota, Southern Res. and Outreach Cent., Waseca. Corn plant populations: A critical component in the yield equation [USDA-NASS] USDA National Agricultural Statistics Service. 2006. Historical track records [Online]. Available at www.usda.gov/nass/pubs/trackrec/croptr04.pdf (verified 1 May 2006). USDA-NASS, Washington, DC. Roger W. Elmore, Professor, Agronomy, Iowa State University Vanotti, M.B., and L.G. Bundy. 1995. Soybean effect on soil nitrogen availability in crop rotations. Agron. J. 86:676-680. d ra White, D.C., J.B. Braden, and R.H. Hornbaker. 1994. Economics of sustainable agriculture. p. 229-260. In: J.L. Hatfield and D.L. Karlen (ed.). Sustainable agricultural systems. CRC Press, Boca Raton, FL. ft Vanotti, M.B., and L.G. Bundy. 1994. Corn nitrogen recommendations based on yield response data. J. Prod. Agric. 7:249-256. Hybrid development and yield advancements have primarily been associated with increasing stress tolerance, i.e. modern hybrids yield more under a resource-limited environment relative to older hybrids. Yield potential per acre has increased dramatically in the past fifty years, while the potential yield per plant has changed little, if any. Hybrids tolerate their neighbors better today and are therefore able to withstand higher plant densities while still producing an ear. Older hybrids have significant lodging and/or barrenness when planted at today’s seeding rates. A significant portion of the observed yield increase over the last several decades is directly correlated with increased plant populations. It takes high seeding rates paired with high yielding hybrids that can tolerate increased plant-toplant competition to maximize yields. Iowa plant populations have increased approximately 425 plants per acre (ppa) per year since 2001. Although plant populations continue to increase, producers and agronomists must consider whether the yield advantage of planting more seed is economically productive. Corn seed prices have increased dramatically. As seeding rates and seed prices increase, adding an additional unit of seed should be determined in light of whether the return is greater than the cost (Elmore, R. and L. Abendroth, 2008). In calculations made during February 2007, we used a corn price of $3.00 per bushel and seed prices ranging between $1.00 and $2.50 per 1,000 seed; this equated to $80 to $200 per 80,000 seed unit. Today, hybrids containing a triple stack of resistant traits are the highest priced seed on the market with retail price projected above $300 per bag this season. ra ft [USDA-SCS] USDA Soil Conservation Service. 1981. Land resource regions and major land resource areas of the United States. Agric. Handb. 296. U.S. Gov. Printing Office, Washington, DC. Introduction d [USDA-SCS] USDA Soil Conservation Service. 1961. Soil Survey of Grant County Wisconsin. USDA-NRCS in cooperation with the Wisconsin Agric. Exp. Stn., Madison, WI. Lori J. Abendroth, Agronomy Specialist, Agronomy, Iowa State University Objectives The objective of this research and presentation is to develop and present recommendations for Iowa producers and agronomists; as well as gain understanding of how and why yield responses to seeding rates vary across locations and years. The following questions will be addressed during this presentation: 1) How are plant population and yield potential related? How has yield potential been increased by corn breeders? 2) What is the optimum seeding rate (or plant population) for maximum yield? 3) What is the optimum seeding rate (or plant population) for economic yield? 4) What response variables (kernel weight, lodging, barrenness, etc.) are changed in addition to yield when seeding rates (or plant population) are increased? 5) What agronomic criteria are important and should be considered when selecting a seeding rate for a specific field? 36 — 2008 Integrated Crop Management Conference - Iowa State University Table 1. Nitrogen applied, established plant population, and grain yield of site-specific research with varying plant populations and nitrogen levels used (Ping et al., 2008). Literature review: Influence of agronomic factors A recent publication (Ping et al., 2008) of research conducted in central Nebraska investigated variable rate nitrogen (pre-plant nitrogen rates ranged from 30 to 150 pounds per acre) and variable plant populations (range of 21,900 to 36,800 ppa) at two locations and two years based on within-field yield zones. Yield zones were predetermined using soil organic matter, seasonal NO3 status, and six years of yield maps. Forty to fifty pounds of sidedress N were applied uniformly across all treatments within a site; only pre-plant N varied based on the yield zones. Neither variable rate nitrogen nor variable plant population improved grain yields (Table 1). In addition, the plant population response was similar at different N levels. d Nafziger (2007) continues to conduct plant population research in Illinois and found similar results in that the yield response to plant population is similar regardless of nitrogen rate. Average Plant Population Grain Yield lbs/a ppa bpa Site 1 Year 2003 Uniform Uniform 119 a† 31900 a 246 bc Variable Uniform 106 b 31900 a 254 a Uniform Variable 119 a 31300 a 242 c Variable Variable Year 2004 Uniform Uniform Variable Uniform Uniform Variable Variable Variable Site 2 123 a 31300 a 251 bc 176 a 32000 a 243 a 173 a 32000 a 248 a 176 a 30800 a 240 a 175 a 30800 a 246 a ra ra Irrigated research in northeast Nebraska (Shapiro and Wortmann, 2006) investigated yield responsiveness to plant population across two row widths (20 and 30 inches) and four nitrogen levels (0 to 225 pounds N per acre). Row width and nitrogen increased yield when evaluated individually, by 4% and 24%, respectively. Surprisingly, plant population did not alter yield levels. Yield levels were relatively low (ranged from 114 to 168 bushels per acre (bpa)). Factors other than plant population likely limited yield at this site. The rate of nitrogen did not affect the yield response to plant population. Nitrogen Year 2003 Uniform Normal 219 a 32000 a 213 a Variable Normal 218 a 32000 a 211 a Uniform High 219 a 37000 a 218 a Variable High 228 a 37000 a 215 a Low 179 a 27000 c 194 a Normal 179 a 32000 b 197 a High 179 a 37000 a 192 a Year 2004 Averaged over all N rates d Seeding rate and nitrogen ft Plant population research has been conducted in surrounding states as well as Iowa. Here, we will examine research published in the last decade (1998-2008) in Illinois, Iowa, Michigan, Nebraska, and Wisconsin regarding some of the agronomic factors that may or may not affect seeding rate responsiveness. During the conference we will discuss our current research in Iowa (2006-2008) in light of these findings and identify differences and similarities. Plant Population Average N ft 6) What environmental criteria are important and should be considered when selecting a seeding rate for a specific field? 2008 Integrated Crop Management Conference - Iowa State University — 37 † Means within a column followed by the same letter are not different from one another. Seeding rate and row spacing Widdicombe and Thelen (2002) determined that the yield response to plant population (range from 23,000 to 36,000 ppa) did not differ based on row width (10, 20, or 30 inches) in Michigan. Farnham (2001a and 2001b) identified a similar response in Iowa where he investigated the impact of plant population (24,000 to 36,000 ppa) and row width (15 and 30 inches) across six locations for three years in Iowa. Overall, yield in 30” rows was greater than 15” rows, 167 and 164 bpa, respectively. Yet, the population response was similar in both row widths. In the research stated above (Shapiro and Wortmann, 2006), the yield response to plant population was consistent across both row widths (20 and 30 inches) also. 38 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 39 Seeding rate and crop rotation Overall environment Researchers in Michigan observed no seeding rate response to crop rotation, although five of the six sites were corn following soybean and one was following corn (Widdicombe and Thelen 2002). Nafziger (2007) does not think increased plant populations will benefit corn following corn more than corn following soybean. Nafziger (2007) recommends 35,000 ppa for Illinois, given favorable growing conditions and productive soils. A lower population (between 25,000 and 30,000 ppa) is recommended on less productive soils or a fairly dry growing season. Yield is less responsive to plant population in yield limiting environments or during stressful growing seasons. Therefore, to optimize yield while managing risk, he recommends higher populations to take advantage of good weather rather than using lower populations to protect against unfavorable weather. ra Wisconsin researchers (Stranger & Lauer, 2006) investigated hybrids with (Bt) and without (non-Bt) resistance to European corn borer (ECB). Hybrids were grown at ten locations over three years. The plant population associated with the highest yield (i.e. maximum yield plant population (MYPP)) varied for Bt and non-Bt corn; 42,300 and 40,000 ppa, respectively (Figure 1). Yields were 4.2% greater when the Bt and non-Bt hybrids were planted at MYPP instead of the recommended 30,000 ppa. Although MYPP was at or above 40,000 ppa, the economically optimum plant population (EOPP) was 33,900 ppa. Maximum and economic yield differ by 8400 ppa (Bt corn) and 6100 ppa (non-Bt corn). Overall, Bt hybrids yielded more yet the plant population needed to maximize yield resulted in greater seed costs; these added costs nullified the extra yield coming from the Bt hybrid. Yield increases usually taper off as population rises above 30,000 ppa; a greater yield increase (bpa) occurs when the population is increased from 25,000 to 30,000 ppa, rather than 30,000 to 35,000 ppa. Farnham (2001a) investigated the impact of plant population (24,000 to 36,000 ppa) and row width (15” and 30”) in Iowa as discussed above. Yield and plant population were correlated linearly with one another at 10 of the 18 site-years; interestingly two of the ten site-years had a negative relationship. One site-year had a quadratic response and the remaining seven locations were nonresponsive to plant population. Farnham summarized these research findings along with additional data and published it the ISU Corn Planting Guide. Recommended plant populations varied based on location and year which suggests the optimum plant population will vary based on growing season and location. ft ft In Michigan, Widdicombe and Thelen (2002) evaluated six hybrids. The hybrids responded differently to plant population although the reason why could not be pinpointed. Hybrid characteristics evaluated were: different ear types (flex/fixed, determinate/indeterminate), plant height, and leaf orientation. Their inability to find causes for the difference in response to increasing plant populations for hybrids with differing characteristics is consistent with research reports from Illinois and Ohio. Stalk integrity and lodging ra Seeding rate and hybrid response Stranger and Lauer (2006) identified greater lodging (22% more) with non-Bt hybrids as population increased compared to Bt hybrids. Across all hybrids, lodging increased from 5% to 16% as plant population increased from 26,000 to 50,000 ppa. Stalk rot was a contributing factor at some locations. Summary points 255 bpa (1)Plant population responses are little affected by neither row widths nor nitrogen rate d (2)Environment and location cause significant variation year to year in optimum plant population 191 bpa d (3)Plant lodging and degraded stalk quality may be greater with increased plant populations (4)Grain yield reduces more when a population is used that is significantly below the optimum population rather than significantly above. 127 bpa Materials and methods – Iowa 2006 to 2008 Site years: 31 total; 12 locations in 2006, 11 locations in 2007, and 8 locations in 2008. 16000 ppa 32000 ppa 48000 ppa Figure 1. Grain yield response of Bt and non-Bt hybrids to varying plant populations; Wisconsin 2002-2004 (Stanger and Lauer, 2006). Data in Figure represent individual plot data. Adapted with English units by Elmore and Abendroth. Locations: Ames (2006, 2007, 2008), Carroll (2006, 2007, 2008), Castana (2007, 2008), Cedar (2008), Charles City (2008), Clarence (2006, 2007), Corning (2008), Hubbard (2006, 2007), Indianola (2008), Keystone (2006, 2007), Lewis (2006, 2007), Nashua (2006, 2007), Sutherland (2006, 2007), Winterset (2008). 40 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 41 Final plant population (ppa) Percent root and stalk lodging at harvest (when present) Percent barrenness (plant with an ear that has no kernels present) Grain moisture (%) at harvest Grain yield (bpa) adjusted to 15% moisture basis Kernel weight (gram) per 100 kernels Percent greensnap (where applicable) d Field management: Fields were planted primarily between April 25 and May 15 during the three years. Conventional tillage (fall and/or spring) was used except at locations where tillage was a treatment (see below). Fertilizer and pesticides were applied appropriately to meet crop demand and control weed pressure. Yield was collected from the center two rows of each four-row plot. Plot design: Plots were arranged in a randomized complete block design (RCBD) with three or four replications. Individual plot dimensions varied yet the majority of sites used plots that were 4 rows wide (10 feet) by 20 feet in length. Treatments: (1)Seeding rate: Varied by location yet half of the locations (15 of 31 site years) had identical treatments: four seeding rates beginning at approximately 31000 seeds per acre and increasing incrementally to 47000 seeds per acre. The complete range in seeding rates used across all 31 locations was 21000 to 47000 seeds per acre. (2)Management practices: Seeding rate was evaluated alone and/or in combination with the following factors at some locations: tillage intensity (no-tillage, strip-tillage/conventional tillage, deep tillage), hybrid genetics (quantity of resistant traits) and relative maturity, cropping system (corn following corn or corn following soybean), and row width (30” spacing or twin row configuration). Data collected: ft At the time of writing this proceeding, the collection and analysis of 2008 data has not been completed. Data will not be analyzed by year; instead all 31 site-years will be analyzed collectively to develop recommendations for Iowa. Yield and overall plant response to seeding rates/plant populations will be discussed relative to known agronomic and environmental criteria. References ra Figure 2. Seeding rate research conducted in Iowa during 2006-2008. Results and discussion Elmore, R. and L. Abendroth. 2008. Seeding rates in relation to maximum yield and seed costs. Integrated crop management newsletter. Iowa State University Extension. 5 May 08. http://www.extension.iastate.edu/CropNews/2008/0503RogerElmoreLoriAbendroth.htm Farnham, D. 2001a. Row spacing, plant density, and hybrid effects on corn grain yield and moisture. Agron. J. 93: 1049-1053. Farnham, D. 2001b. Corn planting guide. Iowa State Extension. PM 1885. Nafziger, E. 2007. Should we increase corn plant populations? The Bulletin newsletter. University of Illinois Extension. http://ipm.uiuc.edu/bulletin/article.php?issueNumber=1 &issueYear=2007&articleNumber=12 Verified 3 November 2008. d ra ft Extended leaf plant height Ping, J.L., R.B. Ferguson, and A. Dobermann. 2008. Site-specific nitrogen and plant density management in irrigated maize. Agron J. 100:1193-1204. Strange, T.F. and J.G. Lauer. 2006. Optimum plant population of Bt and Non-Bt corn in Wisconsin. Agron. J. 98:914-921. Shapiro, C.A. and C.S. Wortmann. 2006. Corn response to nitrogen rate, row spacing, and plant density in Eastern Nebraska. Agron. J. 99:529-535. Widdicombe, W.D. and K.D. Thelen. 2002. Row width and plant density effects on corn grain production in the northern Corn Belt. Agron. J. 94:1020-1023. Acknowledgements Thank you to the following ISU personnel who established and maintained these research trials: Chad Arnold, Jeff Butler, Fred Engstrom, William Fjelland, David Haden, Mark Licht, Ken d ra ft Appreciation is also extended to the ISU Corn Soybean Initiative (CSI), Monsanto, Pioneer, and Mycogen for contributing seed or funding towards this research. Predicting yield before harvest: How does the USDA forecast corn and soybean yield? Greg Thessen, Director, Iowa Field Office, USDA-NASS Introduction Crop production forecasts have two components--acres to be harvested and expected yield per acre. For example, preliminary corn and soybean acreage estimates are made using data obtained from a survey of farmers conducted during the first 2 weeks in June. Expected corn and soybean yields are obtained monthly, August through November, from two different types of yield surveys. Data from the yield surveys reflect conditions as of the first of the month, as data are collected during the last week of the previous month and the first 2 or 3 days of the current month. ft Thank you to the following undergraduate research assistants, graduate research assistants, and staff of the ISU Extension Corn Production program who collected and managed the field and laboratory data: Lesa Andersen, Sarah Baune, Matthew Boyer, Leslie Freehill, Nick Kastler, Wade Kent, Stephanie Marlay, Marcos Paulo da Silva, and Derek Shalla. 2008 Integrated Crop Management Conference - Iowa State University — 43 Crop production forecasts are based on conditions as of the survey reference date and projected assuming normal conditions for the remainder of the season. For example, the assumption of “normal conditions” is that temperatures and precipitation will be at historic averages for the remainder of the season. It is assumed that the first killing frost will occur on the historic average date. The crop maturity and conditions at the reference date are evaluated against the time remaining until the expected frost--if one third of the crop will not reach maturity until the frost date has passed; it is assumed that some frost damage will result. Long-range weather projections are not used as an indicator for final yield. ra Pecinovsky, Jim Rouse, Ryan Rusk, and William Vinson. The reference point for crop forecast surveys is the first of the month, which is also usually close to the mid-point of data collection. Both grower-reported average yields and objectivemeasurement modeled yields contain a measurable forecast error based on the historic difference between these survey estimates and the final end-of-season yield. The review process followed to develop the monthly yield forecasts involves evaluating the relative ranges of the forecast errors of the grower yields and the objective measurement yields and the degree to which they overlap. When NASS states as policy that it is forecasting based on conditions as of the first of the month, it is saying that it will establish yields within the range of the survey estimates. d 42 — 2008 Integrated Crop Management Conference - Iowa State University When forecasting crop yields, NASS does not attempt to predict future weather conditions. Long-range weather forecasts are not used in any forecast models. To the extent that conditions depart from normal, the forecasts also will fluctuate. Procedures used to prepare acreage estimates and yield forecasts are discussed in the following sections. Base for acreage planted and to be harvested The largest single survey NASS conducts each year is the June Agricultural Survey. During the first 2 weeks in June, about 2,400 interviewers contact over 125,000 farmers, either by telephone or in person, to obtain information on crop acreages, grain stocks, and livestock inventories. These producers are asked to report the acreage, by crop, that has either been planted or that they intend to plant, and the acreage they expect to harvest as grain. Data from this survey are used to estimate, among other things, total acres planted to corn, soybeans, and other crops regardless of the intended uses. Preliminary projections of acres to be harvested for grain or 44 — 2008 Integrated Crop Management Conference - Iowa State University ra About 10,000 area segments are selected nationwide for the survey conducted each June with 452 of these segments located in Iowa. Using maps and aerial photos showing the exact location and boundaries of each sample segment, interviewers locate and interview every operator with land inside the segment boundaries to identify crops planted in each field, and to obtain livestock inventory information, and quantities of grain in storage. Before sampling from the list, each farm is classified by various characteristics such as number of acres by crop. Large farms are sampled at high rates. For example, Iowa farms on the list with over 5,000 acres of cropland, or grain storage capacity exceeding 1 million bushels, are selected with certainty. Smaller farms are selected at rates of 1 out of 10 to 50. d About 75,000 farms across the United States are selected from the list to be surveyed during the same time period in June with about 2500 of these farms located in Iowa. Farmers on the list sample are asked to provide total acres planted for each crop on all the land they operate, and quantities of grain stored on their operation. Most of the data from this sample are collected by telephone interviewers. Data from the area and list samples are combined using multiple-frame statistical methodology developed jointly by NASS and Iowa State University, which ensures that all land areas in the United States can be accounted for once and only once. Generally, estimates of planted acres for corn and soybeans from the June Agricultural Survey are not changed until October. However, occasionally the planting season runs late and many fields are not yet planted with the intended crops at the time the June survey is conducted. When this happens, adjustments to planted area estimates may be made at the time of the first yield forecast in August. If a significant portion of the crops are not planted by the time the June Agricultural Survey is competed (like in Iowa for 2008), NASS may re-interview the June survey respondents during late July to determine what was actually planted. The preliminary projections for harvested acres may also be adjusted using data from the August yield surveys or in extreme cases from a special July re-interview survey. Any necessary changes to planted and harvested acreage estimates will be published in the August Crop Production report. Yield forecasts A subsample of farmers who respond to the list portion of the June Agricultural Survey is selected to provide monthly crop yield forecasts. This provides a way to screen farmers so that only those currently growing the commodities of interest are contacted during the monthly surveys. This monthly Agricultural Yield Survey asks the sampled farmers to report what they expect their crops to yield before harvest and actual yields are obtained at harvest. All yield data for an individual report are weighted by the farm’s crop acres for harvest. ft ft Sampling from the area frame is a multi-step process. First, all land in each State is classified into land use categories by intensity of cultivation using a variety of map products, satellite imagery, and computer software packages. These land use classifications range from intensively cultivated areas to marginally cultivated grazing areas to urban areas. The land in each use category is then divided into segments ranging from about 1 square mile in cultivated areas to 0.1 square mile in urban areas. This allows intensively cultivated land segments to be selected with a greater frequency than those in less intensively cultivated areas. Segments representing cultivated areas are selected at a rate of about 1 out of 125. Sample segments in land use classifications with decreasing amounts of cultivated land are selected at rates ranging from 1 out of 250 to 1 out of 500. Objective Yield Surveys are conducted monthly in states that contribute most heavily to total U.S. production of corn and soybeans. These surveys provide information for making forecasts and estimates of crop yields based on counts, measurements, and weights obtained from small plots in a random sample of fields. Sample corn and soybean fields are selected from those identified in the area-frame sample portion of the June Agricultural Survey. In Iowa, 330 corn fields and 240 soybean fields are selected. Observations within each selected field are made in two randomly located plots. Plots include two adjacent rows of predetermined length. ra The sample design for this survey utilizes two different sampling frames. The area frame, which is essentially the entire land mass of the United States, ensures complete coverage of the U.S. farm population. The list frame, a list of known farmers and ranchers, does not provide complete coverage of all farms, but allows the use of more efficient data collection methods. 2008 Integrated Crop Management Conference - Iowa State University — 45 In October, NASS will review several data sources for corn and soybeans, including the farmer reported surveys, satellite imagery, and acreage data reported by producers to the Farm Service Agency (FSA) and may update the area planted and expected acres for harvest in the October Crop Production report. Harvested yield can be thought of as biological or gross yield minus harvest loss. Counts, measurements, and other observations from each sample plot are input to statistical models based on historical data to predict final number of fruit and final weight per fruit. A forecast of gross yield is calculated by multiplying these two components together and dividing by land area. Table 1 shows the forecast variables used to predict the gross yield components for each crop. Table 1. Objective yield forecast variables for number of fruit and fruit weight. Crop corn Component Forecast variable1 ears stalks ears & ear shoots ears with kernels historic average length over husk kernel row length ear diameter plants main stem nodes lateral branches blooms, dried flowers & pods pods with beans historical average pods with beans d soybeans, including seed, are also made using these data. ear weight soybean plants pods per plant pod weight 1 Variables measured are determined by stage of maturity. 46 — 2008 Integrated Crop Management Conference - Iowa State University Plant characteristics used as prediction variables change as the crop maturity progresses. At an early stage, plant counts may be the only data available for forecasting the number of mature fruit. As the crop matures, actual fruit counts can be used, and weights and measurements of the immature fruit are used to predict final weight per fruit. USDA - NASS October Forecast to Final Yield Iowa, Corn 2003-2007 185 185 180 175 Final Final 180 170 175 170 165 165 160 160 155 155 155 160 165 170 August Figure 1 175 180 185 150 155 160 165 170 October 175 180 Final 45 40 185 45 40 35 35 30 30 40 42 44 46 48 50 52 30 35 40 45 50 55 October August Figure 2 NASS will revise estimates of harvested acres if necessary during the forecast season when extreme weather events (flood, drought, hurricane) warrant and supporting data from a survey is available. Again, the goal is to make the production forecasts as accurate as possible. The production forecasts are based on projecting the acres that will be harvested and the final yield per harvested acre. If acres are lost during the forecast season because of weather or disease problems, those yields drop to zero, the acres are classified as planted but abandoned, and acres for harvest reduced. For this reason, it is possible for the production forecast to be reduced without a corresponding drop in forecast yield per acre. It is also possible for the yield per acre to increase during adverse periods if acres for harvest are abandoned and classified as not for harvest. Data on which to base changes in harvested acres come from the yield forecast surveys when sample fields are taken out of production or the operator reports acres no longer being considered for harvest. USDA-NASS strives to provide the agricultural community with estimates and forecasts that are accurate, objective, reliable, and timely. This is accomplished by conducting surveys throughout the growing season and after harvest is complete. Security measures are used to prevent leaks of this market-sensitive information which is published in the Crop Production report each month and is available on the NASS website at www.nass.usda.gov. d d Potential accuracy of each month’s forecast for these crops is dependent on the crop maturity at the time of the forecast and future weather. When maturity lags normal patterns, number of pods, ears, etc., is based on number of plants and fruiting positions rather than actual number of fruit. Thus, when maturity lags, the forecasts become more variable because the expected number of fruit can differ from the final. However, the primary source of forecast error occurs when final end of season fruit weights differ from the historic average because fruit weight cannot be fully determined until crop maturity. A comparison of the August and October forecast to the final NASS estimate for corn and soybeans is shown in Figures 1 and 2, respectively. 50 50 ft ra Average pod weights prior to crop maturity are based on historical averages. In normal years, much of the soybean crop has matured by the October survey, so current-year pod weights are used. Corn objective yield survey forecasts are based on estimates of number of ears and average ear weight. The ear count forecasts are accurate early in the season. When the crop is late developing, the August projection of ears is based on a model using plant population. Historical average ear weights are used until ears are present to measure. Kernel row length models are then used to project ear weight until crop maturity. 55 55 ra ft The estimate of number of soybean pods per acre from the Objective Yield Survey is usually very consistent from month to month and accurate when the bloom period has ended. Pod count forecasts usually stabilize with the September survey. USDA - NASS October Forecast to Final Yield Iowa, Soybeans 2003-2007 USDA - NASS August Forecast to Final Yield Iowa, Soybeans 2003-2007 Final The same plots are revisited each month until the crop is mature. At that time, the plots are harvested and final counts and weights are obtained. After the entire field has been harvested by the farmer, one-fourth of the sample fields are revisited and two more plots are laid out. The grain left on the ground in these plots is picked up and weighed to provide a measure of harvest loss. USDA - NASS August Forecast to Final Yield Iowa, Corn 2003-2007 2008 Integrated Crop Management Conference - Iowa State University — 47 48 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 49 A fresh look at some new and alternative forages Stephen K. Barnhart, Professor and Extension Forage Specialist, Agronomy, Iowa State University smooth bromegrass timothy red clover orchardgrass corn alsike clover tall fescueswitchgrass white clover reed canarygrass oats Kentucky bluegrass cereal rye birdsfoot trefoil ft alfalfa Collectively, they make up 90+ % of the forage produced and used for pasture, hay and silage in the state. Among these commonly used species, new varieties become available as genetic improvements are brought to the market place. ra Additionally, there are several forage species, which are promoted and sold in Iowa that are not widely used, and some that are essentially ‘new-to-Iowa’. Information on adaptation and production management of these uncommon and new-to-Iowa species is often limited. Some new species and a few of the new varieties of the ‘old traditional’ forages are tested in Iowa State University Variety Trials and as entries in some of the forage breeding programs being conducted. Unfortunately, some have essentially no 3rd party, objective adaptation or production data for Iowa growing conditions. Following are brief descriptions of the traits and likely adaptation some of the ‘old traditional’ species with new varieties and some not-so-familiar forage species that Iowa producers have been asking about in the last few years. In some cases specific adaptation observations and use suggestions are made. d d ra ft Iowa producers grow and manage 40 to 50 different species of plants for forage, cover crops in row crop fields and as components of soil erosion control and buffer strip practices. The most commonly used are: Legumes Alfalfa (Medicago sativa L.) is probably the most planted and used legume in Iowa. Its stand life is normally 3 to 5 years under harvest management, with stand density often limited by root and crown diseases. Alfalfa is not suited to poorly drained or low fertility or pH sites. It is versatile, being used for hay, silage or grazing. Many varieties are suited to Iowa growing conditions. Among the traits introduced in alfalfa varieties over the past 10 years or so are: grazing tolerance, wheel traffic tolerance, higher nutritive quality, heterosis, and a tolerance to the feeding of the insect pest, potato leafhopper. There is great interest within the alfalfa industry to pursue more hybridization, resistance to other races of Aphanomyces root rot. Glyphosate-tolerant varieties have been on the market and are currently in ‘legal limbo’. There is continued work on other transgenic traits for alfalfa. Information about alfalfa varieties is available from many sources, including the ISU Alfalfa Variety Test web site noted at the end of this article. Kura Clover - (Trifolium ambiguum Bieb.) is a deep rooted, rhizomatous, long- lived perennial legume for pasture mixtures. It has potential for hay, silage or pasture. There is interest in using Kura clover as a ‘living mulch’ / cover crop. Seed production has been limited. Kura clover has very poor seedling vigor and establishes very slowly ( 2-3 years). Bloat potential is expected to be similar to that of red clover. Varieties suggested are: ‘Endura’, ‘Rhizo’ and ‘Cossack’ Rhizomatous Birdsfoot trefoil - (Lotus corniculatus L.) A trefoil capable of spreading with rhizomes was released in Missouri a few years ago. The variety is named ‘Steadfast’. There has been no seed supply in recent years, so is not likely to be a viable forage in the near future. d Cicer Milkvetch - (Astragalus cicer L.) is a very winter-hardy, long-lived, spreading, non-bloating, legume more common in the western plains states. It is similar in nutritive value, but lower yielding than alfalfa. Cicer milkvetch has grown satisfactorily in Iowa. Annual Lespedeza - (Kummerowia stipulacea -- Korean lespedeza ; and Kummerowia striata -striate lespedeza) are short, hardy legumes that tolerate lower pH and fertility than alfalfa or clovers. They are used successfully in pastures and produce best in mid- to late-summer. Most varieties produce and shatter some seed by autumn in Iowa. They may not produce enough shattered seed to produce full stands of ‘volunteer’ plants in later years. Though at least one variety was developed in Iowa in the 1940’s, most production remains in southern Iowa, mid-south states. ‘Legend’ and ‘Marion’ are the newest Midwest varieties available. Berseem Clover - (Trifolium alexandrinum L.) also called Egyptian clover; is a fast growing clover used as a winter annual in the southern US. It has been used as a summer annual legume in Iowa, but grows as an annual and will winterkill.. In good growing seasons, multiple harvests possible, but growth and yield is limited in dry seasons. Field Pea is a short-season forage cover crop that does best when planted in very early spring. Field pea is usually grown with cereal grains intended for silage harvest. The pea improves the protein content of the forage. Harvest decisions should be made on the quality and yield of the associated cereal forage. Forage Soybeans – Historically, ‘Southern type’ varieties that grow vegetative much of the season have been used in mixture with short, grain sorghums or corn to improve the protein content in silage of the mixed crop. USDA has released several tall varieties for forage (silage), the variety ‘Derry’ is best suited for Iowa. The extra yield comes the last 4-6 weeks of the growing season. Little or no seed develops. Grasses - temperate/cool-season ft ra ft Red Clover - (Trifolium pretense L.) - is considered to be a short lived (seeding year + 1 or 2 years), upright clover that tolerates lower pH and poorer drainage than does alfalfa. Red clover can be used for hay, silage or grazing. Stand life is limited by root and crown diseases. Red clover often produces blooms in the seeding year. Red clover plants can ‘volunteer’ readily from hard seed. Medium red clover is considered a multiple-cut clover (2-3 cuts in production years), and is most often used for hay and pasture. Newer varieties have somewhat better production (10-30%) over ‘common’ red clover. Some have slightly better yield in the 3rd growing season, compared with varieties of 10 years ago. Some improved varieties for the upper mid-west states include Marathon, Impact, Duration , Starfire, RedStart, RedlanGraze II, Amos, Cinnamon Plus, & Scarlet. Mammoth red clover is considered to be a ‘1-cut’ clover and has historically been used as a ‘plowdown’ legume. 2008 Integrated Crop Management Conference - Iowa State University — 51 Tall Fescue - (Festuca arundinacea Schreb.) is a perennial, cool-season, sod-forming grass; used for harvested forage, pasture and turf. It establishes relatively rapidly, and is the grass species of choice to ‘stockpile’ for autumn and winter grazing. A problem often encountered with established tall fescue stands is the presence of an endophyte fungus that adversely affects livestock performance. It is the presence of the endophyte that imparts some of the competitiveness to the plant. Careful management of early growth and seedstems is important to minimize livestock use problems. Low endophyte and endophyte free varieties have had persistence problems in the southern U.S. states, but perform nearly as well as infected varieties in Iowa. Tall fescue grows throughout Iowa but is most prevalent in the So. 1/2 of the state. The newest element in the fescue arena is the use of a ‘novel endophyte fungus’ that imparts the vigor to the fescue plant without the ‘bad effects’ of the endophyte alkaloids on the livestock. The variety sold with the novel endophyte is ‘Jessup-MAXQ’. The novel endophyte may not be needed in Iowa; we can grow fungus-free varieties. ra White Clover - (Trifolium repens L.) - is a shallow-rooted clover that spreads by stolons and shattered seed. It can suffer some dormancy during hot, dry summer conditions and can winterkill in cold, open winters. White clover is compatible with low-growing grasses, and is best suited for grazing, where it is tolerant of close and frequent grazing. Bloat is a potential risk when grazing white clover. ‘Ladino’ is a large-leaved type of white clover that may be more productive than the smaller leaved types, but is usually shorter-lived. Newer varieties of the medium-leaved white clovers are being marketed form Europe and New Zealand ( examples ‘Will’ & ‘Alice’). ‘White Dutch’ clover is the ever-present, common , small-leafed white clover that dominates in most permanent pastures. Reed Canarygrass - (Phalaris aurndinacea L.) is a perennial, cool-season, slowly-spreading bunchgrass that is adapted to a wide variety of soil conditions, and is quite tolerant of poorly drained sites. It is used for harvested forage, pasture and soil conservation. Once established, rapid spring growth and relatively low palatability make it difficult to manage in mixed stands. Once grazed or cut, summer regrowth is better accepted. Reed canarygrass probably has the best summer growth of the commonly used cool-season grasses. It is relatively slow to establish. Newer varieties have been developed with low levels of alkaloids to improve digestibility. Low alkaloid varieties include: ‘Venture’, ‘Palaton’, ‘Rival’, Chiefton’ and ‘Marathon. d 50 — 2008 Integrated Crop Management Conference - Iowa State University Annual Ryegrass - (Lolium multiflorum), with its sub-type ‘Italian’ ryegrass has very rapid seedling emergence and growth. It does not generally overwinter well in Iowa. Some varieties produce seedheads in seeding year. If allowed to mature and shatter seed, annual ryegrass can regrow as volunteer plants in later years. This trait has led to annual ryegrass becoming an annual grassy weed in small grains in some parts of the country. Perennial Ryegrass - (Lolium perenne L.) is a very high quality cool-season grass with relatively rapid seedling emergence and vegetative growth. Most of the ‘forage-type’ varieties have been imported from Europe and Australia/New Zealand, and have had a history of winterkill the first winter. ‘Summer slump often occurs in hot, dry summers. The more promising new varieties frequently have 15-40%+ plant survival. ‘Turf-type’ varieties have been developed in the US and show reasonably good winter survival but relatively low forage yield potential. Turf-type varieties often have a tall fescue-like ‘endophyte fungus’ problem. Many forage-type varieties are available. Use ft Intermediate Wheatgrass - (Thinopyrum intermedium Host; Barkworth & Dewey) is a vigorous, spreading, winterhardy grass. It has relatively rapid seedling development, and can yield more in early stand development than smooth bromegrass. It heads slightly later than smooth bromegrass, and may have better late-summer and autumn regrowth than that of smooth bromegrass. Iowa research is limited. Warm-season perennial grasses Switchgrass - (Panicum virgatum L.) is a tall-grass prairie perennial (3-6 ft), characterized as a slow-spreading bunchgrass. It is a popular tall prairie grasses because of seed characteristics. It is relatively unpalatable compared to big bluestem. Switchgrass heads in early to mid-July. Improved forage varieties; ‘Trailblazer’, ‘Sunburst’. Also adapted; ‘Cave-in-Rock’, ‘Blackwell’, ‘ Pathfinder’. ra There is interest in switchgrass as a perennial biomass crop for energy production. Big Bluestem - (Andropogon gerardii Vitman) is a 3 to 6 foot perennial grass, native to the Midwest U.S. It is a slow-spreading bunchgrass and was an important component of the native, tall-grass prairie. Big bluestem is very palatable. Its fluffy seed makes it difficult to plant. Heading dates are late-July/Aug. Suggested varieties: ‘Rountree’, ‘Kaw’,’ Bonanza’ , and ‘Gold Mine’. Indiangrass - (Sorghastrum nutans L., Nash) is a perennial (3-6 ft) bunchgrass, and a component of the native, tall-grass prairie. Fluffy seed makes it difficult to plant. It is palatable, and remains vegetative in the summer, heading in late-Aug/Sept. Varieties include ‘Rumsey’, and ‘Cheynne’. d Eastern Gamagrass - (Tripsacum dactyloides L.) is a tall, warm-season, perennial, bunchgrass that was a very minor component of the native, tall-grass prairie. It has vegetative and regrowth characteristics similar to sorghumXsudangrass hybrids. Eastern Gamagrass is very palatable. Researchers and producers are learning together how to best establish it, and how much defoliation it will tolerate without losing vigor. Seed lots are now available that have been ‘pre-chilled’ to enhance more uniform establishment. Currently available varieties; ‘Pete’, ‘Iuka’, a brand, PMK-24. Warm-season, summer annual grasses Foxtail Millet - (Setaria italica L., Beauv.) also called German, Siberian, or hay millet is an annual, warm-season grass; used as harvested or grazed forage. It produces one summer growth (vegetative 1-2 ft, with seedhead 2-3 ft). It is the best of the ‘millets’ for an emergency hay crop. Foxtail miller can become a weedy grass if allowed to produce mature seed. Japanese Millet - (Echinochloa crusagalli var. frumentacea Link, Wight) is a relatively coarse (stemmy) summer annual forage that can be used as fresh cut forage, hay, silage, or pasture. There is very little regrowth if first growth is allowed to reach maturity, but, if cut at vegetative growth stage, good regrowth yields are more likely. Japanese millet is closely related to the grassy weed barnyard grass, so avoid allowing seed formation. Hybrid Pearl Millet - (Pennisetum americanum L.) is a multiple-cut, warm-season annual; used for fresh cut forage, silage, or pasture (rotation grazing is recommended if grazed). It resembles sorghumXsudangrass hybrids in plant structure, but has somewhat slower regrowth than sorghumXsudangrass hybrids. It does not produce well in cool summer seasons. There is no risk of hydrocyanic acid (Prussic acid) poisoning with hybrid pearl millet. Forage Chicory - (Cichorium intybus) is considered a perennial weed in many areas;. It is a palatable ‘herb’ in pastures and will contribute to multiple grazings per year. Chicory is widely adapted, and establishes relatively rapidly. It may remain vegetative in the seeding year or produce seedstems. The second year and later growth will produce seed stems which must be grazed or clipped to maintain leafy regrowth for grazing. The variety ‘Puna’ was developed in and is being imported from New Zealand. Other varieties-from Uruguay and France- ‘Lecerta’ and ‘Forage Feast’ are available with varying flowering and winterhardiness traits. Chicory can persist on a site if allowed to produce viable seed and volunteer seedling establishment. ft Meadow Bromegrass - (Bromus riparius Roem. Schult) is a perennial bromegrass with good seedling vigor and adaptation in Iowa. Research in Montana indicates that it has a better regrowth pattern than smooth bromegrass. The variety ‘Regar’ is a selected variety developed from a Turkish plant introduction. Iowa production data is very limited. 2008 Integrated Crop Management Conference - Iowa State University — 53 Bermudagrass (Cynodon dactylon L.) is a warm-season perennial grass used extensively in the south central and south eastern U.S. states. Most varieties are established, vegetatively, using ‘sprigs. Bermudagrass spreads quickly, and has good summer production where adapted. It is not considered to an adapted, long-term perennial in the northern states. and is not generally considered to consistently over-winter in Iowa. There are a few instances of scattered Bermudagrass plants surviving in very mild winters , and a few plants may persist for several years. Surviving plants begin recovering well in June under average Iowa conditions. There are some Bermudagrass varieties and blends that can grow form seed, at about 1/10 the cost of sprigs. Seeded varieties can be very productive in the seeding year, but often winterkill. ra objective, 3rd party performance information when making variety selection decisions. Teff (Eragrostis teff) Teff is an annual grass used as a grain crop in some parts of the world. It has been used as forage in the U.S. for about the past 20 years. Its seed is very small, so recommendations are for a seeding rate of 5 to 6 lbs/A, and a planting depth of 1/8 to ¼ in. Planting should be delayed until mid- to late-May through July. One to 3 cuts of hay can be obtained. Several commercial varieties are available. Experience with it in Iowa is limited. References d 52 — 2008 Integrated Crop Management Conference - Iowa State University The ISU forage variety testing results from recently completed trials are available on the Iowa Crop Improvement Assn. www site. http://www.croptesting.iastate.edu/alfalfa/results/ . For more information, contact: Stephen K. Barnhart Extension Forage Agronomist Iowa State University, Ames IA (515) 294-7835 e-mail: sbarnhar@iastate.edu 54 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 55 Practical considerations in developing bioenergy crops Emily A. Heaton, Assistant Professor, Agronomy, Iowa State University Kenneth J. Moore, Professor, Agronomy, Iowa State University Steven L. Fales, Professor, Agronomy, Iowa State University ra ft Biofuels represent a significant challenge and opportunity for agriculture. Producing liquid fuels from cellulosic biomass affords a number of potential environmental benefits. Biofuels result in lower greenhouse gas emissions than fuels derived from petroleum. Growing perennial biomass crops reduces soil erosion and sequesters more carbon than annual crops grown for grain or biomass. Corn and sorghum are crops that have high near-term potential as annual biomass crops. Dedicated biomass crops with very high yields will produce more fuel per acre, helping to balance land for food and fuel. Switchgrass and Miscanthus are perennial species that have been broadly evaluated as potential biomass crops, but will benefit from further development for widespread use. New crops and cropping systems developed specifically for bioenergy production will be necessary to meet biofuel production targets. Bioenergy crops should be developed that use inputs efficiently, have high and stable productivity, have positive environment impact, and are compatible with existing cropping systems. Most importantly, biomass crop portfolios must be developed that allow for sustained energy supply throughout the year. Introduction The U.S. Departments of Agriculture (USDA) and Energy (DOE) released a feasibility study in which they evaluated the potential of cellulosic biomass for meeting a goal of replacing thirty percent of transportation fuels with ethanol derived from biomass by 2030 (Perlack et al., 2005). They estimated that this would require approximately one billion dry tons of feedstock to accomplish. They estimated present feedstock available from agricultural lands to be 194 million dry tons annually and evaluated alternative scenarios for increasing availability to the billion ton goal. Crop residues, such as corn stover, and dedicated energy crops are anticipated to be the largest sources, however a disproportionate amount of biomass is expected from a relatively small acreage devoted to dedicated biomass crops. d d ra ft Summary Major multi-national energy companies are now heavily investing in biomass energy for a variety of reasons including 1) pressure to reduce CO2 emissions; 2) mandated requirements for green energy production and 3) increasing difficulty in extracting petroleum from the earth. Concomitantly, they have seen record profits as the price of oil increased over the past 2 years, causing ability and pressure to put money into renewable energy research and production. It is important to recognize that these companies are used to working with geologists to find the fuel they need; now they need to work with agronomists! Growing biomass in conjunction with traditional food crops will require careful and intensive management. There is no way we will saturate demand for biomass from agriculture as we have traditionally done with food crops, and energy producers will require contracts for biomass 56 — 2008 Integrated Crop Management Conference - Iowa State University d Biomass crops may create opportunities to diversify cropping systems and optimize landscape use based on spatial variation. In many crop producing regions, cropping systems are relatively simple, consisting of just a few monoculture crops grown in various sequences. Introduction of biomass crops into these rotations may produce positive rotation effects related to nutrient, moisture, and pest management. It may be possible to introduce perennial biomass crops into long-term rotations with annual grain or biomass crops to restore soil carbon balance and improve soil quality. By providing a market for cellulosic biomass, marginal land that is currently in row crop production could be diverted to perennial biomass crops that are more environmentally appropriate. Crop geography of biomass production The primary goal of biomass crop production is the capture and conversion of sunlight into chemical energy. The efficiency of this conversion depends on a number of factors some of which can be altered through management and others that cannot be managed. The potential production of any crop depends on climatic and edaphic factors associated with the region in which it is grown. Climatic factors such as precipitation, temperature and solar radiation determine where crop species can be grown and their potential yield within a given climatic region. Crop adaptation is limited by growing season, temperature and moisture stress, and in many cases, photoperiod (Nelson, 1996). Soil quality also influences adaptation and yield potential of biomass crops. The inherent productivity of soil is affected by chemical, physical and biological properties which interact with climate to determine potential productivity of a site. Soils with physical limitations such as low water holding capacity, high bulk density, and poor drainage negatively influence plant growth. Soil fertility is also important, particularly with respect to plant nutrition and factors that adversely affect plant growth such as high and low pH, and accumulation of phytotoxic elements such as sodium and aluminum. Dedicated bioenergy crops ft Because yield density of available ethanol feedstock will likely be a major criterion in considering the location of biorefineries, it is reasonable to assume that they will be located in regions where biomass production potential per unit area is relatively high. These areas are generally characterized by adequate precipitation for crop production, a moderate to long growing season, and soils capable of sustaining a high level of productivity. Within the U.S., the highest biomass producing areas are located in the humid temperate and subtropical regions which extends east from about 98Ëš W longitude. Other considerations of likely importance will be the existence of current cropping systems that are compatible with biomass production and agricultural and transportation infrastructure. What are the species that will be used to provide bioenergy feedstock and to what degree will they vary by production region? This section will review some key grasses in use as early energy crop species while the next explores trait considerations in the development of new dedicated energy crops. ra Figure 1. Example of a biomass crop portfolio to meet target feedstock tonnage throughout the year for a given region. Graphic courtesy of Ceres, Inc. 2008 Integrated Crop Management Conference - Iowa State University — 57 Table 1. Basic information on early and developing grass energy crops species in the United States. Establishment method Life cycle Established agronomics Established U.S. markets Typical biomass yield (t DM/ha)1 Seed Annual Yes Food, grain ethanol 11 – 22 Sorghum Seed Annual Yes Food, feed 15 – 27 Switchgrass Seed Perennial No Forage 7 – 22 d ra ft delivered throughout the growing season. How will this be done? We suggest that it will be done by developing crop portfolios that allow expanded and more efficient use of the growing season. Further, it will be done in areas of the country that have the infrastructure for high-output production and distribution, i.e. the Midwest. It is just a matter of time, policy and of course, profit. Crop Perennial No Not developed 22 – 34 Corn Miscanthus Rhizomes (Bean et al., 2006, Pyter et al., 2007, Schmer et al., 2008) 1 Annual grasses Corn (Zea mays L.) As mentioned previously, the dominate biofuel at present is grain ethanol from corn grown intensively on an increasing number of acres in the U.S. (NASS, 2007). Corn grain is a logical first biofuel feedstock since it has long been used for production of food grade ethanol around the world, and has established economic and agronomic infrastructure. Modern corn hybrids are the product of more than a century of dedicated crop breeding and are dramatically different from their wild progenitors (Jauhar, 2006). Corn has been bred to respond strongly to inputs of irrigation and fertilizer, as well as coupled with dedicated pest management regimes, leading to unprecedented grain yields. Sorghum (Sorghum bicolor (L) Moench) ra Sorghum is an early annual biomass crop that seems to combine the domesticated advantages of corn with the low-input benefits of perennial grasses. Like corn it has established markets and a well-developed portfolio of crop management tools. Both crops were domesticated by early agrarian societies and have been adapted to a broad range of production environments. Sorghum is traditionally used in areas considered marginal for corn production and is known for its low input requirements, particularly of nitrogen fertilizer and water. This makes it an attractive candidate as an environmentally, energetically and economically favorable alternative annual biofuel feedstock, especially in areas of the U.S. outside of the Corn Belt. d Of the different types of sorghum crops, sweet sorghum and forage sorghum have gained most attention as cellulosic biomass feedstocks. Sweet sorghum has the attraction of high ethanol yields possible from both fermentable sugars and stover biomass. New lines of forage sorghum that may be considered inferior for livestock production have such high biomass yields as to recommend them for development into cellulosic feedstock varieties. Particularly promising in this regard are the photoperiod sensitive varieties that require day length cues to switch from vegetative to reproductive growth. When grown in higher latitudes, these varieties do not receive such a cue and will keep producing vegetative biomass until low temperatures terminate growth for the season. A major advantage of sorghum for an early biomass feedstock is its established presence as a crop in the U.S., and the familiarity of farmers with its successful production. That said, sorghum produced for cellulosic biomass will likely require different agronomic management practices than growers are accustomed to using for grain, sugar or forage production, and these practices are only beginning to be researched. The need for cellulosic biomass to be dry, for example, will likely influence harvest time and method, and maximizing tons per acre instead of optimizing forage quality and quantity might change fertility recommendations. Perennial grasses Switchgrass (Panicum virgatum L.) A perennial grass native to much of North America, switchgrass is probably the best known cellulosic biomass crop in the U.S., thanks in part to its specific mention in a U. S. State of the Union address (Bush, 2007). A major component of prairie ecosystems, switchgrass has long been used as a warm-season forage and later as a conservation tool for erosion control. Because of its ability to produce biomass more consistently than many other native U.S. species over multiple locations and years, and it’s favorable environmental qualities, switchgrass was identified as a leading candidate for bioenergy production (McLaughlin & Kszos, 2005, Parrish & Fike, 2005). The U.S. Dept. of Energy began investigating it as a model bioenergy species through a variety of research programs over 20 years ago (DOE, 2006). While more developed than many other species now being investigated as energy crops, switchgrass is still far from a completely domesticated crop. It is only the recent and exponentially growing interest in renewable energy from plant biomass that has forced the recent proliferation of switchgrass improvement efforts. There are several characteristics that lend switchgrass to cellulosic biomass production, some of which have been alluded to previously. It is perhaps fair to say that just as sorghum represents an annual species that already combines the convenient attributes of a widely used domesticated crop with the low-inputs and high yields of an energy crop, switchgrass represents a perennial species with similar, but less developed capability. It already has the capacity for use in modern production agriculture on a large scale, coupled with moderate biomass yields and promising genetic variation for improvement (Missaoui et al., 2005, Taliaferro, 2002). Seed is currently available for purchase in the U.S., planting and harvesting can be done with conventional forage equipment, and some herbicides have been labeled for use in switchgrass (Nyoka et al., 2007). The environmental benefits of switchgrass on soil, water and habitat quality are well documented (Giuliano & Daves, 2002, Ichizen et al., 2005, Lemus & Lal, 2005, Lin et al., 2005). As a perennial, planting is required only once, and if properly managed, a switchgrass stand can be maintained for an indefinite period with low input demands (Parrish & Fike, 2005). ft ft Despite the concerns over using corn for food vs. fuel and the environmental impact of continuous corn production on U.S. cropland, it is one of the few existing crops today that is readily available and can be immediately deployed for ethanol production (Table 1). There is little doubt that corn will remain an integral component of the energy crop species portfolio for the foreseeable future. 2008 Integrated Crop Management Conference - Iowa State University — 59 ra Because corn has been purpose bred as a food crop, it is not surprising that it is not optimized as an energy crop. The economic and energetic inputs that have been acceptable or tolerable in food crops come under heavy scrutiny if applied to energy crops as they reduce the net energy produced in the biofuel while increasing both the carbon footprint and production cost of the feedstock. New efforts are now underway to breed corn varieties that require fewer inputs, as well as those that are dual purpose food/biofuel varieties, relying on increased fermentable sugars in the grain and a higher fraction of stover that can be converted to ethanol via cellulosic conversion pathways. It is technically feasible to grow switchgrass with success, but production for bioenergy is not yet optimized. Further, no real economic or agronomic crop support infrastructure yet exists for it or any other dedicated energy crop. Switchgrass has traditionally been grown on only limited acreage in the U.S., and the majority of U.S. farmers are as of yet unfamiliar with its management (Jensen et al., 2007). Improving the agronomic and economic management of switchgrass for bioenergy has been a major focus of U.S. research, with the goal of informing grower practices. Recent evidence indicates this strategy may be working. Schmer et al. (2008) found that field scale production and grower familiarity dramatically enhanced crop productivity, leading to yields of biomass and energy over 90% greater than those found at the research plot scale for LIHD plantings (see Intensive vs. extensive biomass production, above). d 58 — 2008 Integrated Crop Management Conference - Iowa State University Most switchgrass varieties used today have undergone only a few breeding cycles or have been simply increased from wild populations. There is wide genetic variability to be exploited in switchgrass and dedicated breeding programs have made rapid improvements through traditional and molecular approaches (Bouton, 2002, Taliaferro, 2002, Vogel et al., 2002). Giant Miscanthus (Miscanthus x giganteus). Another perennial grass under development as a cellulosic biomass crop is the sterile hybrid Miscanthus x giganteus, often referred to as Giant Miscanthus. A relative newcomer to U.S. energy crop considerations, Giant Miscanthus has been investigated in Europe in the much d Though Giant Miscanthus is sterile and cannot be selectively improved in the same way as switchgrass, the Miscanthus genus has much genetic variation to exploit through traditional and molecular breeding, and in fact this has been done for the crop’s cousin, sugarcane (Amalraj & Balasundaram, 2006). Miscanthus research in the U.S. and the EU now emphasizes crop breeding and development of commercially viable agronomic practices. Biomass crop ideotype Development of crops bred specifically for cellulosic biomass is in its infancy. Which plants are naturally best suited to biomass production? We have already discussed some early leading energy crops and alluded to factors favoring their success in this regard. It must be realized, however, that crops used at this early stage are as likely to be promoted from luck or legacy as they are from merit. However, we are now at a time when genomic understanding enables plant breeding at an unprecedented rate and the outcomes of the Green Revolution may be weighed with the perspective of time, thus we have the opportunity to design a sea change in global agriculture. A careful consideration of crop traits useful to biomass feedstock production from first principles seems prudent. Factors that should be evaluated in that analysis are outlined here. Generally, an ideal biomass crop must be characterized by the resource efficient conversion of sunlight energy into usable carbohydrate energy. Efficiency: Biomass crops must store as much carbon per unit input of water, fertilizer, light, heat, etc. as possible to allow them to be cheaply and sustainably produced. Grasses with the C4 photosynthetic pathway have inherent efficiencies that lend them to cellulosic biomass production; perennials in this group have added benefits over annuals in providing ecosystem services (Long, 1994, Samson et al., 2005). Productivity: High yield density (unit biomass/unit land area) is required to a) make harvest and transport economically viable; b) allow biorefineries to realize economies of scale; and c) reduce opportunity costs from competing land uses. Flexibility: Biomass feedstock must be available upon demand and therefore available in sufficient and changeable quantities year round. Crop mixtures comprising different life cycles and maturity times must be developed to support this demand and minimize need for storage or drying. Stability: Energy security will depend on a stable supply of feedstock within and between growing years. Crops and crop mixtures must minimize risk of yield loss from pests, disease or weather. ft ra Of the crops discussed here, Giant Miscanthus is probably least compatible with the existing production agriculture infrastructure in the U.S. Digging, sorting, transporting and planting rhizomes dramatically increases planting costs over traditional seed based crops. This cost is partially offset by the higher biomass yields from Giant Miscanthus and the low annual production costs. Like switchgrass, Giant Miscanthus has long stand lifetimes, low input requirements and well documented environmental benefits (Schneckenberger and Kuzyakov, 2007, Semere and Slater, 2007a, Semere and Slater, 2007b). In England the crop is commercially used in electricity production through co-firing with coal, and here a successful agricultural industry has developed, supported by economic incentive packages and federal research. This has led planted acreage to increase by approximately 300% every year since the support programs began (DEFRA, 2006). 2008 Integrated Crop Management Conference - Iowa State University — 61 Sustainability: In a carbon-conscience and resource constrained future, biomass crops must have a favorable environment impact, including both a positive greenhouse gas and energy balance. Ecosystem services such as carbon sequestration, water and nutrient cycling and wildlife habitat will add value and utility to the system. Compatibility: To meet mounting demand, biomass crops must be adopted and scaled up rapidly. This necessitates new crops be developed and introduced in tandem with agronomic practices that make them easily incorporated into the existing agricultural infrastructure in the U.S. ra ft same way as switchgrass has been in North America. Likely a product of hybridization between Japanese M. sacchariflorus and M. sinensis, this triploid is not capable of producing fertile seed and is typically planted using rhizome cuttings (Hodkinson et al., 2002, Lewandowski et al., 2000, Nixon et al., 2001). Giant Miscanthus was advanced as an energy crop in the EU in part because this sterility, coupled with a non-spreading growth habit, mitigated risk of weediness or pollen outcrossing with compatible species. Following years of testing in multi-location trials around the EU, Giant Miscanthus was shown to produce consistently high biomass across a range of conditions with minimal inputs, and at temperatures and latitudes beyond the normal growing range of warm season grasses (Jones & Walsh, 2001). When evaluated in the U.S., Giant Miscanthus produced record yields, on average 2-4 times more biomass than switchgrass (Heaton, 2006, Heaton et al., 2008). Future research needs and challenges Replacing a significant proportion of transportation energy with cellulosic biofuels will require development of highly productive energy crops. The crops described above represent near-term alternatives and will require significant improvements in biomass productivity to remain viable as energy crops in the future. A rational long-term approach will be required to develop alternative, high-yielding biomass crops specifically designed for energy and industrial uses. A significant research effort is needed to identify alternative plant species that produce higher biomass yields and have desirable biomass traits, develop cultivated varieties of alternative species through genomics and plant breeding approaches, and develop appropriate crop management practices and systems for producing dedicated energy crops. d 60 — 2008 Integrated Crop Management Conference - Iowa State University Acknowledgements Adapted from Biorenewable Energy: New Opportunities for Grassland Agriculture. Proc. of the International Grasslands Conference, Hohhot China (2008) Bean, B., T. McCollum, K. McCuistion, J. Robinson, B. Villareal, R. VanMeter, and D. Pietsch. 2006. Texas Panhandle Forage Sorghum Silage Trial. Texas Cooperative Extension and Texas Agricultural Experiment Station. Bouton, J. 2002. Bioenergy Crop Breeding and Production Research in the Southeast (ORNL/ SUB-02-19XSV810C/01). University of Georgia. ft Bush, G.W. 2007. State of the Union Address. http://www.whitehousegov/stateoftheunion/2007/ initiatives/sotu2007.pdf. DEFRA. 2006. Creating Value from Renewable Materials A strategy for Non-food Crops and Uses. Department of Environment, Food and Rural Affairs. Farrell, Alexander E., Richard J. Plevin, Brian T. Turner, Andrew D. Jones, Michael O’Hare, and Daniel M. Kammen. 2006. Ethanol can contribute to energy and environmental goals. Science 311:506-508. ra Giuliano, W.M., and S.E. Daves. 2002. Avian response to warm-season grass use in pasture and hayfield management. Biological Conservation 106:1-9. Heaton, E.A. 2006. The Comparative Agronomic Potential of Miscanthus x giganteus and Panicum virgatum as Energy Crops in Illinois, University of Illinois. Heaton, E.A., F. G. Dohleman, S. P. Long, and T. B. Voigt. 2008. Meeting U.S. biofuel goals with less land: the potential of Miscanthus. Global Change Biology (In review). 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English, J. Menard, M. Walsh, and D. de la Torre Ugarte. 2007. Farmer willingness to grow switchgrass for energy production. Biomass and Bioenergy 31:773-781. Jones, M.B., and Walsh M. 2001. Miscanthus for Energy and Fibre. James and James Ltd., London. Lemus, R., and R. Lal. 2005. Bioenergy crops and carbon sequestration. Critical Reviews in Plant Sciences 24:1-21. Lewandowski, I., J. C. Clifton-Brown, J. M. O. Scurlock, and W. Huisman. 2000. Miscanthus: European experience with a novel energy crop. Biomass and Bioenergy 19:209-227. Lin, C.H., R. N. Lerch, H. E. Garrett, and M. F. George. 2005. Incorporating forage grasses in riparian buffers for bioremediation of atrazine, isoxaflutole and nitrate in Missouri. Agroforestry Systems: 63:91-99. Long, S.P. 1994. The application of physiological and molecular understanding of the effects of the environment on photosynthesis in the selection of novel “fuel” crops; with particular reference to C4 perennials. In Plant Production on the Threshold of a New CenturyCongress of the 75th Anniversary of Wageningen Agricultural University. McLaughlin, S.B., and L. A. Kszos. 2005. Development of switchgrass (Panicum virgatum) as a bioenergy feedstock in the United States. Biomass and Bioenergy 28:515-535. ft Amalraj, V.A., and N. Balasundaram. 2006. On the taxonomy of the members of ‘Saccharum complex’. Genetic Resources and Crop Evolution 53:35-41. 2008 Integrated Crop Management Conference - Iowa State University — 63 Missaoui, A.M., A. H. Paterson, and J. H. Bouton. 2005. Investigation of genomic organization in switchgrass (Panicum virgatum L.) using DNA markers. Theoretical and Applied Genetics 110:1372-1383. NASS. 2007. National Agriculture Statistics Service. http://www.nass.usda.gov. Nelson, C. J. 1996. Physiology and developmental morphology. p. 87-125. In L. E. Moser, D. R. Buxton, and M. D. Casler (ed.) Cool-Season Forage Grasses. Agronomy No. 34. American Society of Agronomy, Madison, WI. ra References Nyoka, B., P. Jeranyama, V. Owens, A. Boe, and M. Moechnig. 2007. Management Guide for Biomass Feedstock Production from Switchgrass in the Northern Great Plains. Sun Grant Initiative North Central Center, South Dakota State University. Parrish, D.J., and Fike J.H. 2005. The biology and agronomy of switchgrass for biofuels. Critical Reviews in Plant Sciences 24:423-459. Perlack, R.D., L.L. Wright, A.F. Turhollow, R.L. Grahm, B.J. Stokes, and D.C. Erbach. 2005. Biomass as feedstock for a bioenergy and bioproducts industry: The technical feasibility of a billion-ton annual supply. USDA-DOE. ORNL/TM-2006/66. Pyter, R., T. B. Voigt, E. A. Heaton, F. G. Dohleman, and S. P. Long. 2007. Giant Miscanthus: Biomass Crop for Illinois. p. 39-42. In J. Janick and A. Whipkey (ed.). Issues in New Crops and New Uses, ASHS Press, Alexandria, VA. d 62 — 2008 Integrated Crop Management Conference - Iowa State University Samson, R., S. Mani, R. Boddey, S. Sokhansanj, D. Quesada, S. Urquiaga, V. Reis, and C. H. Lem. 2005. The potential of C-4 perennial grasses for developing global BIOHEAT industry. Critical Reviews in Plant Sciences 24:461-495. Schmer, M.R., K. P. Vogel, R. B. Mitchell, and R. K. Perrin. 2008. Net energy of cellulosic ethanol from switchgrass. Proceedings of the National academy of Sciences 105:464-469. Schneckenberger, K., and Y. Kuzyakov. 2007. Carbon sequestration under Miscanthus in sandy and loamy soils estimated by natural C-13 abundance. Journal of Plant Nutrition and Soil Science-Zeitschrift Fur Pflanzenernahrung Und Bodenkunde 170:538-542. Semere, T., and F. M. Slater. 2007a. Ground flora, small mammal and bird species diversity in miscanthus (Miscanthus x giganteus) and reed canary-grass (Phalaris arundinacea) fields. Biomass and Bioenergy 31:20-29. d ra ft Tilman, David, Jason Hill, and Clarence Lehman. 2006. Carbon-negative biofuels from low-input high-diversity grassland biomass. 314:1598-1600. Trends in precision agriculture Matt Darr, Assistant Professor, Agricultural and Biosystems Engineering, Iowa State University Introduction Precision agriculture is no longer a generic term defining our desire to more precisely manage equipment and agronomic inputs. As precision agriculture enters its sixteenth year, it has become an industry within itself and features a suite of hardware and software components aimed to improve efficiency in all areas of production agriculture. As we look back on the past sixteen years we can see clear innovations in precision agriculture that have helped shape the future direction of this industry. During its infant years, precision agriculture was focused on methods to collect production data across the field using newly available GPS technology. This was mainly focused on yield monitoring and grid soil sampling to better understand trends and management zones. During the mid to late 1990’s precision agriculture shifted focus towards machine control products for variable rate fertilizer placement and steering assistance, including lightbars and autosteering. The past five years have brought on another precision agriculture revolution focused on automating sections of our implements and requiring ever increasing accuracy from our GPS receivers. ft Taliaferro, C. 2002. Breeding and selection of new switchgrass varieties for increased biomass production. (ORNL/SUB-02-19XSY162C/01). Oak Ridge National Laboratory. 2008 Integrated Crop Management Conference - Iowa State University — 65 This past history clearly indicates the future direction of precision agriculture products and user requirements. Automation has provided growers a tremendous benefit in enhancing field efficiency, reducing input cost, and allowing for advanced production practices that were previously unachievable. Adoption of automation systems will continue to increase as will the development and release of new automation products. At the heart of all automation systems is the GPS receiver and it will continue to play a major role in driving the future potential of new systems. ra Semere, T., and F. M. Slater. 2007b. Invertebrate populations in miscanthus (Miscanthus x giganteus) and reed canary-grass (Phalaris arundinacea) fields. Biomass and Bioenergy 31:30-39. The role of GPS in improving accuracy GPS receivers are the core component of any precision agriculture machinery system and will continue to be the limiting factor on machinery performance. Less accurate GPS receivers will lead to the poor performance of autosteering systems and disappointing results of autoswath systems for sprayers and planters. No matter how advanced the control hardware is on the tractor or implement, poor quality GPS will always limit the overall machine performance. d 64 — 2008 Integrated Crop Management Conference - Iowa State University By receiving information from satellites, GPS receivers are able to calculate the position of the receiver on earth. Errors though are common in GPS receivers and are caused by a wide range of factors including weather, satellite orbit accuracy, and the local environment. These errors are reduced by using a GPS Correction or Differential GPS (DGPS). DGPS systems are the norm for precision agriculture products, but the source of the GPS Correction signal can still vary significantly. As the signal quality increases so does the system cost. 66 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 67 Iowa’s FREE statewide RTK network (IaRTN) Currently there are five types of GPS Correction solutions used in precision agriculture products: Although RTK receiver costs have come down in recent years, the investment into RTK equipment is still quite high both from a cost and complexity standpoint. If producers are operating over a multi-county area, multiple base stations are often needed. The management time needed to maintain multiple RTK base stations is often unrealistic for a single producer. To offset this challenge, RTK Networks began to form around 2004 which allowed producers to subscribe to an RTK correction service that was maintained by a secondary company or group of equipment dealers. The costs of these subscriptions are often very similar to the cost of a Dual Frequency subscription and the adoption of this service has been high around areas where it is provided. For producers not located near and RTK network provider or in an area where line-ofsite to the RTK base is not possible, the Iowa Department of Transportation’s new RTK Network (IaRTN, www.iowadot.gov/rtn/index.html) is a viable competitive solution. ra • Dual Frequency GPS: Dual frequency GPS correction offers significant advances over single frequency correction and provides a much more stable correction signal. The dual frequency component allows the receiver to better correct for atmospheric errors and these receivers also use a high quality reference network rather than the free WAAS network. This comes at a cost as the user must pay a yearly subscription fee to access the dual frequency reference network. This fee ranges from $750 – $1500 per year and is sold through OmniSTAR (HP and XP) and John Deere (SF2). Dual frequency though will provide pass-to-pass accuracies of ±4 inches or better which is ideal for precise autosteering for planting. d • GLONASS: GLONASS is the Russian version of GPS and is currently operating with 17 active satellites. Many US based precision agriculture vendors are offering receivers that are both GPS and GLONASS compatible. The addition of GLONASS satellites offers several unique advantages. First, by receiving data from additional satellites, the receiver is able to calculate a more precise position. Also, a higher density of satellites in the receiver’s view makes it possible to maintain adequate accuracy when operating near large tree lines. This is difficult to accomplish with GPS only systems. Many new GPS receivers are GLONASS compatible and typically require only a software activation to get them running. • RTK: RTK correction is the most accurate type of GPS correction because it utilizes a reference station located very close to the GPS receiver. RTK is not new and is often characterized as very accurate but very expensive. When using RTK the user must buy an RTK capable receiver for their tractor as well as an RTK base station. The user is also responsible for moving the base station near enough to the tractor so that they can maintain line of sight communication. While this can be costly and a management hassle, RTK is the only type of GPS correction that can provide year-to-year position stability. This enables a host of new production methods including controlled traffic, strip tillage/fertilization/planting, and extremely precise autosteering and autoswath control. IaRTN is a network of 78 RTK base stations that are located through the state. Each of the base stations is connected to a central data server that is managed and maintained by the Iowa DOT. Access to the RTK correction data has been made available, free of charge, to any public or private entity. These base stations have been organized as a Continuously Operating Reference Station or CORS for short. Since the data server is centrally located, two-way radios can no longer be used to provide the correction signal. In CORS receivers a cell phone is required to receive the RTK correction. With the wide distribution of base stations throughout the state, this investment by the DOT has guaranteed that anywhere a cell phone signal is present RTK service is available at no charge. Since the CORS network uses cell phone service to transmit the correction signal, standard GPS receivers cannot utilize this resource. The GPS receiver must be specifically sold as a CORS enabled receiver in order to access the network. A dedicated cell phone service is typically used for CORS receivers and requires a data only plan which can range from $25 - $50 per month. Both CORS and traditional RTK Networks offer tremendous opportunities for achieving high accuracy GPS while minimizing the user cost and complexity. ra ft • Single Frequency GPS: Single frequency GPS receivers also use the free WAAS correction service, but these receivers have significantly better antennas and more advanced electronics than low cost receivers. These receivers will typically produce ±12 inches accuracy during pass-to-pass field operations which is suitable for non-critical guidance operations including tillage, spraying, and seeding/drilling. Single frequency receivers are also the standard receiver used for variable rate fertilizer application. d • Low Cost: Low cost GPS receivers use a free correction service called WAAS which is available throughout the US. These receivers are very low cost, have a small antenna area, and are generally not very accurate. They are used exclusively for mapping broad areas for management zone delineation or for soil sampling. They can also be used for yield monitoring, but will provide reduced accuracy along the boundaries of a field where tree shading is significant. ft Current GPS correction solutions 68 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 69 Calibration of NIRS whole grain analyzers for amino acid measurement in corn Connie L. Hardy, Program Specialist, Extension Value Added Agriculture Program, Iowa State University Glen R. Rippke, Laboratory Manager, Grain Quality Lab, Iowa State University Charles R. Hurburgh, Jr., Professor, Agricultural and Biosystems Engineering, Iowa State University ft In food and feed products, near infrared spectroscopy (NIRS) is used to measure an increasing number of chemical parameters that have traditionally been measured by analytical chemistry. The use of NIRS is driven by its speed and relative low cost, thereby allowing users to accurately measure nutrient components and other factors of interest in a matter of seconds versus several hours or days for traditional lab results. Calibration of NIRS analyzers relies on good representative sample sets and consistent reference chemistry; calibration is, in itself, a painstaking process but, once done, accurate calibrations provide rapid, reliable measurements in daily operations. ra Rapid measurement of amino acids in raw and processed grain is becoming increasingly important in balancing livestock rations. National Organic Program standards are expected to change in 2010 to disallow synthetic amino acid supplements in organic feeds. When the standards change, sufficient amino acids must be supplied by the organically grown feed ingredients. With the development of high methionine corn varieties in organic breeding programs, the ability to rapidly measure methionine not only makes the corn breeding process significantly quicker and less expensive, but it will allow livestock feeders to accurately balance rations by knowing amino acid levels in corn. NIRS measurement of amino acids in corn and soybeans has been attempted by several scientists, but it has not succeeded because of the high correlation between the total protein content and the typical amino acid level. In typical corn, for example, methionine usually represents 0.200.25 percent of the total protein. When typical corn is then used to calibrate NIRS analyzers, the resulting calibration simply estimates the typical amount of methionine and cannot identify and measure samples where methionine is higher or lower than its typical level. Therefore, the calibration is not measuring the amino acid, but instead the amino acid level is implicitly calculated using the measurement of total protein. d d ra ft Walter A. Goldstein, Research Director, Michael Fields Agricultural Institute The organic corn breeding program coordinated by Michael Fields Agricultural Institute is developing organic lines of corn with increased levels of methionine, lysine, and cysteine. This program offered a unique set of corn varieties in which amino acid levels were deliberately manipulated to break the correlation with total protein. These unique corn varieties, grown at four Midwestern locations during two crop years (2006 and 2007), provided the set of samples necessary to calibrate NIRS to accurately measure methionine and lysine, two important limiting amino acids in poultry and swine rations. 70 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 71 Calibrations were developed for two whole-seed NIRS transmission analyzers (Bruins OmegAnalyzer G and Foss Infratec™ 1241 Grain Analyzer). Calibration data is shown in Table 1. Prediction of fermentable starch content by nearinfrared spectroscopy Table 1. Correlation of amino acid measurement with NIR spectra and total protein levels Allison Burgers, Graduate Research Assistant, Food Science and Human Nutrition, Iowa state University Measuring the starch content of corn allows ethanol plants to know how much ethanol can be produced from a specific lot of corn. The developments of quick and easy starch measurement methods are important in maximizing the ethanol yield of corn. Measurement of starch content in corn has been done through several laboratory procedures. Fermentable starch best indicates the amount of ethanol produced by the dry-grind method. Conventional laboratory fermentable starch measurement can take hours to days to complete. ft ra d Validation with an independent set of samples (2008 crop) will show if these calibrations are capable of measuring corn samples that were not previously included in the calibration set. With agricultural crops, such as corn, variation due to climate and new genetics affects the spectral interpretation of the grain; therefore, annual checks with new crop samples are necessary to maintain calibration accuracy and broaden the scope of the calibrations. Introduction There is a need for rapid and easy methods to identify the suitability of individual corn lots for dry-grind ethanol production. Near-infrared spectroscopy (NIRS) is a rapid nondestructive technique that is able to measure organic substances in minutes. NIRS could be useful in predicting the amount of fermentable starch in corn samples. ra Coefficient of determination (R ) is often used as a measure of accuracy by comparing NIR spectra to the reference measurement of the selected amino acid. In this case, lysine and methionine have R2 of 0.73 – 0.84, significantly higher than the correlation of each amino acid to the total protein measured. With R2 values in this range, these calibrations are suitable for genetic screening in corn breeding programs (high vs. low genetic evaluations), according to the criteria in AACC Method 39-00, Guidelines for Near Infrared Calibration Development (AACC, 2000). Cysteine became more reflective of protein only (R2= 0.797), but this amino acid is less important in ration formulation than lysine and methionine. 2 Charles R. Hurburgh, Jr., Professor, Agricultural and Biosystems, Iowa State University Objectives The objective of this study was to develop a preliminary NIRS fermentable starch calibration using spectra and reference data from Illinois Crop Improvement Association, and then compare the fermentable starch calibration to the MLR analysis of combinations of Iowa State University predicted values of protein, oil, starch, and density. Materials and methods d ft Lysine Methionine Cysteine Range (%db) 0.26-0.53 0.14-0.39 0.14-0.37 Coefficient of determination (R2) with: Omega spectra Infratec spectra Total protein 0.837 0.842 0.390 0.746 0.730 0.542 0.783 0.787 0.797 Near infrared (NIR) spectra from a FOSS Infratec 1229 Grain Analyzer (FOSS Group, www.foss. dk) was obtained for 249 corn samples. Laboratory fermentable starch measurements from the Illinois Crop Improvement Association were also obtained from the 249 corn samples and were used as the reference data. A fermentable starch partial least squares (PLS) calibration relating fermentable starch content to NIR spectra was developed. A multiple linear regression (MLR) including combinations of current NIR measurements (protein, oil, starch and density on a 15% moisture basis) was also used to predict fermentable starch content. Both the PLS and MLR models included 237 samples. Leave-one-out, full cross validation, was used to validate the calibration models. The first external validation was conducted using 26 samples representing a wide range of composition. More validations are planned for the future. Calculations involving the PLS and MLR models were obtained using The Unscrambler 9.7 (CAMO Inc., www.camo.com). 72 — 2008 Integrated Crop Management Conference - Iowa State University ra A PLS based fermentable starch calibration for Infratec NIRS units was developed using ethanol yield reference data from Illinois Crop Improvement Association. MLR analysis with predicted values of oil, starch and density to predict ethanol yield resulted in similar validation statistics to the new PLS calibration. The PLS model was slightly more precise, but the MLR model may be more practical for actual use. The constituent calculation performed better than the spectra calibration in validation. Implementing a constituent calculation is easier and more economical than implementing a new NIRS calibration, for similar SECV’s. Any NIRS unit can use constituent regression. Acknowledgements POET, LLC Iowa State University Grain Quality Laboratory d Illinois Crop Improvement Association Gregory S. Bennet, Iowa Grain Quality Initiative, Iowa State University Charles R. Hurburgh, Jr., Professor, Agricultural and Biosystems Engineering, Iowa State University Situation Expansion and rapid introduction of new transgenic events will be critical elements in increased grain production, which is needed to fill rising world food and energy demands. The US approval process for biotech products is likely to continue to operate faster than that of our major customer nations, potentially creating market disruptions, and artificial barriers to trade. Most likely, new GM events will be used to create increased yield, although GM quality trait events are also being developed. A workable quality management system framework, supported by specific procedures and practices as needed to satisfy individual markets, could provide the customer assurance necessary for US production to move forward with fewer problems. ft Conclusions ft The PLS calibration had poor results in predicting corn ethanol yield from the 26 external validation samples, with an SEP=0.40 and a R2=0.28. The MLR component model gave consistent results to calibration cross validation. The best combination in validation was protein and starch with an SEP=0.044 and a R2= 0.88. Methodology to insure U.S. genetically modified (GM) grain sales into approved foreign markets—Integrating ISO traceability standards with agricultural quality management systems (QMS) ra The current NIR calibration factors produced similar validation statistics (based on the R coefficient of determination and the SECV-standard error of cross validation) as the new NIR calibration for fermentable starch. The NIR calibration for fermentable starch had a R2 of 0.863 and a SECV of 0.025, while the MLR for the combination oil, starch, and density had a R2 of 0.80 and a SECV of 0.030. All combinations for MLR analysis (protein, oil, starch, and density) had similar results for SECV and R2. 2 Introduction background The Iowa Grain Quality Initiative group, have been developing the theory and practice of traceability of grains, from farmer and receiving elevators to the end users, for several years. Iowa State University has also played a major role in the ongoing development of the ISO 22006 standard, quality management systems for production agriculture. This project incorporates previous ISU work into a quality management based structure with accompanied suggested supporting documentation for corn and soybean production and its bi-products (e.g., DDGS). We are creating a methodology that does not mandate changes, but one that accounts for traceability and flow of essential data in specific cases. The traceability of all grains, especially GMOs (to include partially and incompletely approved GMO varieties), will become increasingly important to retain the value of traits or segregate them from commercial grain marketing channels due to customer requirements. d Results and discussion 2008 Integrated Crop Management Conference - Iowa State University — 73 Iowa State scientists have been developing the theory and practice of traceability for agricultural products. This project will incorporate these results into a management structure (NOVECTA’s QPMS and ISO 22005/22006), and potential operating practices for corn and soybean production and marketing. Because customer perception (rather than scientific reality) is a major element of the GM concerns worldwide, the existence of an organized and practical process by which US-only approved events can be grown/handled should generate favorable public relations. In addition, costs of testing and other more costly interventions could be minimized. The best Quality Management System (QMS) applications are those that start in response to a business problem, and gradually demonstrate their value over time in cost/benefits and efficiency. For example, incompletely approved GM is best first addressed with a set of guidelines and best practices, with more specific steps/documentation in cases of more stringent demands (e.g. 74 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 75 • Process map of corn production operations (to include DDGS), seed to user, showing points at which control or documentation is needed (in varying intensity as the situation dictates) to maintain purity assurances. This can be applied either to the incompletely approved GM to bulk markets, or to the non-GM for specific markets. We have already contributed to the creation of an internationally accepted process (operations) mapping procedure), and are currently applying it to a feed-to-milk production chain. Ultimately, a supply chain’s success is defined by delivering products (appropriately traceable) to users in the condition and manner promised, which is a total system consideration. Any overlooked operation adds to the uncertainty that products will be as desired, with the purity as required, and with minimum impact on surrounding producers. This project will provide a comprehensive traceability standardization infrastructure (transparency of critical data, as needed throughout the supply chain). This will also include compliance and cost/benefit measurement tools that will be formally incorporated within NOVECTA’s offered services. • Checklist methodology for self-assessment and/or third-party assessment. Materials d The materials to be used will include NOVECTA’s QPMS program and the introduction of the new, internationally accepted, and recognized ISO 22000 Food Safety Management System with the new 22006 Production Agriculture series. ISO 22006 blends the strengths of interactive supply chain communications (data flow transparency), with NOVECTA’s QPMS prerequisite program, and another internationally recognized system—Hazard Analysis and Critical Control Point (HACCP) system. By means of auditable requirements, ISO 22006 combines ISO standardization and NOVECTA’s QPMS prerequisite program, which will promote and accelerate the exportation of US GMO grains and their co and bi-products. In addition, participating farmers will utilize ISU created compliance and cost/benefit templates and spreadsheets used to analyze and interpret data. Methods and procedures Performance measures are at the operational and evaluation levels. Operational outputs are specific items (with supporting explanation, support and user interface) to be used in setting up the system. Protocol measurement tools will delve into greater details of the new protocol (of the blended QPMS and ISO standards). Many of the following are nearly or already completed and include: ft • Recordkeeping—quality manual style template that can be user configured to the level of detail needed for a given case. This project will not develop or promote the application of a complete ISO-formatted quality management system, but all the items created will be of the style and format that could be incorporated in an ISO system if desired. Evaluation measurement outputs are in the form of two interrelated spreadsheets and analyses, i.e. traceability compliance scorecard and the cost-benefit spreadsheet. The traceability compliance scorecard represents effectiveness of the protocol, while the cost-benefit spreadsheet evaluates its costs efficiency. Data for both spreadsheets are derived from protocol specifications and participating farmers. ra ra This project will create a cost effective framework protocol for documenting production of either incompletely approved GMO corn or contracted non-GMO corn and soybeans so that essential data will be available to satisfy specific customer needs. The overall goal is to provide US corn and soybean producers increased access to foreign markets, especially for incomplete or partially approved GMOs and GMO co- and bi-products (e.g. DDGS). • Example procedures for critical operations following process map. Project results Development of a protocol (ISO) to help facilitate exportation of US corn and soybeans (and corn co and bi-products), and the ability of the protocol to be audited and trained. This protocol framework comprises: • Develop process maps for corn and soybean production/marketing. • Design a self-study checklist for users to evaluate their present practices. Traceability compliance scorecard set-up and analysis; case study examples presented. The three category areas of interest are: • Create example sets of work instructions/procedures for case study situations; in this case production of new GM corn varieties, assuming 2-4 scenarios with appropriate export status (approved). d Objectives ft 0.5% GM versus 5.0% GM allowances). The tracking/monitoring of raw materials through to customer processing/products is a basic strength of the QMS process, without requiring any more effort and recordkeeping than the specific situation warrants. This project will not design or require an unknown QMS system to be incorporated for farmer use. It will take NOVECTA’s already developed and accepted QPMS and create an export focused protocol that integrates ISO 22005/22006 standards: For the goal of facilitating corn and soybean exports. • Develop a basic producer-oriented traceability instruction and training program, either selfstudy or to be offered through private contractors. • Present the cost-benefit spreadsheet format and analysis with case study examples. This will offer comparisons of production costs tied to purity levels required. 76 — 2008 Integrated Crop Management Conference - Iowa State University The traceability scorecard—provides an effectiveness evaluation of traceability compliance; i.e., comparing the standard (specified—required documentation, procedures, and data) to what is actually accomplished. An example is given below. This can be as complex or simple as the situation and the process map warrant. 2008 Integrated Crop Management Conference - Iowa State University — 77 The cost-benefit spreadsheet—provides an extensive, but not exhaustive, statistical summation that focuses on soybean specific traceability production cost components and revenue data, as applied to varying purity levels of crop production (for comparative purposes). Table 2. Example of the cost-benefit spreadsheet Table 1. Example of a traceability scorecard Back Ground Information 3 1.00 1.00 1 1 3 = farmer + 2 entities A = Accuracy (degree of conformity and/or d measurement parameters; determined by tests, audits, etc.) *Σ 3) Communications (Producer/Buyer) A) Production Nomenclature (pts.) (i) Unit size (ii) Product (iii) Other inputs/Byproducts B) Attribute(s)/Trait(s) (pts.) (i) Data/process(s) of interest (ii) M easurements (iii) Test M ethodology 0.978 1.00 1.00 1 1 1 1 1.00 1.00 2 3 1.0 3.0 0.50 1.00 200 4 185.0 3.1 0.93 0.78 15 50 0.98 3 0.9800 13.5 2.2 0.9600 0.98 0.9750 3 45.0 1.0000 0.90 0.98 2.0 0.73 0.9796 0.9949 0.90 0.67 1 3 1.0 3.0 1.00 1.00 8 4 4.8 3.2 0.60 0.80 7 3 5.2 2.1 0.74 0.70 0.98 20 4 15 3 0.9700 14.9 3.7 13.0 2.0 0.98 0.75 0.93 0.87 0.67 0.9780 0.9980 2 4.5 2.0 0.90 1.00 25 3 22.0 2.4 0.88 0.80 50 3 46.5 2.1 0.93 0.70 0.960 0.980 General Information Crop Planted Crop Variety Planted Purity Level (Required) Crop Acres GIS Acreage Data Grain Yield Previously Planted Crop in Field Type of Trace System Trait(s) and/or Attribute(s) of Interest Other Hourly Wage Information M anagement Labor M eeting, Off Season Contract or Hired Professional Other 0.9898 5 Accuracy Range (Min, Max) 0.9980 Weighted Average S core 0.901 0.895 S td. Trace 1 Trace 2 Trace 3 Trace 4 1 Bill Smith 2 3 4 5 ft 1 1 Input cells are shaded Measure Units Corn % acres n/a bu/acre n/a 200 ra ft 3 1 Personal Information ID Number Name Address Phone # Email Other d 1 entity Difference 1 ra 2) Performance M easurement Entity/Parameters A) Primary Entity (farmer, etc.) (i) Inputs (pts.) (a) Seed purity-98.0% (ii) Operations (pts.) (a) Chemicals data (b) Storage (c) Cleanouts (d) Inspections crop/field (iii) Tests (pts.) (a) Field tests (A) (b) Laboratory tests (A) (iv) Administrative (pts.) (a) Training periods (b) Data collection (c) Inspection, records (v) Certification (pts.) (a) Organic (b) ISO B) Buyer inspections (i) Operational (pts.) (ii) Administrative (pts.) (iii) Tests (A) C) Third-Party inspections (i) Operational (pts.) (ii) Administrative (pts.) (iii) Tests (A) D) Grader (pts.) 0.980 y ac ur D = Depth 1 = farmer 2 = farmer + Measured (actual) Item cc A data points) th ep D h dt measurements and/or a re B = Breadth (actual number of B *Σ y ac ur Std (required) IPT Trait(s) / = Σ 1) Controlling Std (contract/Regs.) Attribute(s) Success A) Seed Purity (98%) Scorecard (e.g., (i) Output Purity ± 0.002-0.005 organic product, fair(ii) Other purity data (pts.) wage, pasture-fed, B) Tolerance Level (pts.) etc.) (i) Other tolerance data cc A a re th ep D th ad re B y ac ur cc A h t ep D h dt B Scorecard Matrix Operating Assumptions Grain Hauling, Semi Interest, Carry-on Operating M oney Capital Interest Personal travel mileage Personal travel meal expense Personal travel overnight expense Other 195 Soybeans None None Corn XYZ 5.0% 200 Corn XYZ 2.0% 200 Corn XYZ 1.0% 200 Corn XYZ 0.1% 200 195 Soybeans New GM O 195 Soybeans New GM O 195 Soybeans New GM O 195 Soybeans New GM O $/hr $/hr $/hr $/hr $25.00 $15.00 $40.00 $50.00 $0.00 $25.00 $15.00 $40.00 $50.00 $0.00 $25.00 $15.00 $40.00 $50.00 $0.00 $25.00 $15.00 $40.00 $50.00 $0.00 $25.00 $15.00 $40.00 $50.00 $0.00 $/mile %/yr %/yr $/mile $/day $/day $0.250 8.00 6.00 $0.500 $50.00 $100.00 $0.00 $0.250 8.00 6.00 $0.500 $50.00 $100.00 $0.00 $0.250 8.00 6.00 $0.500 $50.00 $100.00 $0.00 $0.250 8.00 6.00 $0.500 $50.00 $100.00 $0.00 $0.250 8.00 6.00 $0.500 $50.00 $100.00 $0.00 78 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 79 Grain storage, storage cost and training module Howard E. Shepherd, Extension Program Coordinator, Iowa Grain Quality Initiative, Iowa State University Storage analysis ft With the expansion of the ethanol industry in Iowa in 2005 the Iowa Grain Quality Initiative saw the need to evaluate quality management practices and grain storage practices impacting grain movement to ethanol industry. This presentation describes the response of the Iowa Grain Quality Initiative to the rapid expansion of Iowa’s ethanol industry. As more corn is used locally in ethanol fuel production, less is available for export, feed applications and other processing. This has led to changes in grain transport, on-farm grain storage and the function of local grain elevators. ra The target of the IGQI training module is on-farm grain storage, which was clearly defined by a 2006 survey of the Iowa Ethanol industry as the primary source of corn. The survey indicated 62 percent of the corn was coming directly from the farm to the ethanol plant, and that this share would not change as production capacities increased. The 2006 survey of ethanol plants showed the ethanol plants are quality sensitive: moisture contents above 18% and mold/sprout damage levels above 10% are typically rejected. Most plants choose to buy US Grade #2 Yellow Corn at or below 15%. The fact ethanol plants store, on the average, about 5% of their annual corn inventory can cause ethanol production variability if received corn is out of the quality structure. Both moisture and damage levels affect how well the corn will perform in the formation process. Dry corn stores well with a minimal amount damage, even over several month. Also, dry corn is easier to grind in mills using a hammer mill to break corn. In 2007 Iowa Farm and Rural Life Poll surveyed on farm gain storage for the IGQI. The “2007 Survey Report on Grain Storage and Transportation,” reported that twelve percent of the Iowa Farmers intended to construct on-farm storage over the next three years, with an average of 30,000 bushels of new capacity. The addition of on-farm storage was a direct response to the demand for corn by the ethanol industry. Delivery of corn from on-farm storage will require greater attention to quality management and year long. This longer storage time will require better up front conditioning, and cleaner bins, and better air flow processes for storage. Also, the data from the Iowa Farm and Rural Life Pool indicated that over 70% of producers are not aware of the increased quality needs of the ethanol industry. d d ra ft Introduction Evaluation of Iowa data form the National Agricultural Statistic Service, and Iowa Department of Agricultural and Land Stewardship for 2005 and 2006 gave harvest acres and yield and commercial storage information. The data showed on farm storage and commercial storage and carry over stock and projected yield, a projection of a little over one half billion bushels of covered storage would be needed in the state of Iowa to maintain quality levels in stored grain. 80 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 81 Storage tools Grain, oilseed, and biofuel outlook for 2009 The Grain Storage, Storage Cost and Training Module was developed including three concepts: The over all design of the module is a flow model for decision making on what is needed to develop a storage site and what equipment would be best for the site. The grain flow model leads to a decision maker of what it will cost to construct storage options. The final section is market decision tools for cost of storing grain. The training module can be accessed from the Iowa Grain Quality Initiative web site, www.iowagrain.org. Chad Hart, Assistant Professor, Economics, Iowa State University Lasley, P., Korshing, P., and Arbukle, J. 2008. 2007 Survey report on grain storage and transportation. Iowa farm and rural life poll. Pm-2049 ra Acknowledgments GROWMARK®, Inc. – FS Grain Systems Brochure Hawkeye Steel Products, Inc – Conrad American Brock® Grain Systems d GSI Group ft Edwards, W., 2007. Grain storage alternatives: an economic comparison. Ag decision maker – a2-33 Overall, compared to earlier estimates corn yields were increased in the major producing states as shown in Figure 1. Illinois was bumped up 5 bushels per acre, while Minnesota and Nebraska yields were increased by 4 bushels per acre. Looking at the number of ears per acre, record ear counts were seen across most of the upper Midwest. In fact, Kansas and Nebraska were the only states that were not at record ear counts. ra ft Hardy, C., 2006. Sourcing corn for ethanol: impacts of local processing. Value added agriculture program report The latest round of USDA updates to its World Agricultural Supply and Demand Estimates and Crop Production reports were updated on Oct. 28th. Corn acreage is now estimated at 85.9 million acres, with harvest expected on 78.2 million acres. Soybean area is estimated at 75.9 million acres planted and 74.4 million acres harvested. National yield estimates are 153.9 bushels per acre for corn and 39.5 bushels per acre for soybeans. Corn production is projected at 12.033 billion bushels, 39 million bushels below the September estimate. For soybeans, production is estimated at 2.938 billion bushels, 4 million above September estimates. These estimates still point to the 2nd largest corn crop and 4th largest soybean crop the U.S. has ever seen. d References U.S. crop supply Figure 1. Corn Yields (bushels per acre) and the Change from Last Month. Source: USDA, NASS 82 — 2008 Integrated Crop Management Conference - Iowa State University Soybean yields across most of the northern U.S. have been adjusted downward since September, with Illinois being the major exception. Nationally, soybean yields are projected to be 1.2 bushels below last year’s level, but the shift of over 10 million acres to soybeans in 2008 has boosted soybean production. 2008 Integrated Crop Management Conference - Iowa State University — 83 at 205 million bushels. The projections for 2008 show corn ending stocks falling to 1.088 billion bushels and soybean ending stocks holding at 205 million bushels. Thus, the crop stock situation looks to remain very tight. Figure 2. Soybean Yields (bushels per acre) and the Change from Last Month. Source: USDA, NASS For Iowa, corn harvested area is now projected at 12.5 million acres with an average yield 172 bushels per acre. This leads to an estimated production of 2.15 billion bushels, down 218 million bushels from last year. Soybean harvested area is estimated at 9.6 million acres. With yields projected at 46 bushels per acres, Iowa is expected to produce 441.6 million bushels of soybeans. This would be a decline of just over 7 million bushels from 2007. The increase in soybean area this year was pretty much offset by the yield decline we experienced this year. At the end of September, USDA updated the grain stocks situation. In that update, both corn and soybean stocks were increased for the 2007 crop year. Corn stocks for 2007 were upped 48 million bushels, based on lower feed, food, and seed use. The total corn ending stocks for 2007 are set at 1.624 million bushels. Soybean stocks for 2007 were increased 65 million bushels, based on higher production and lower crushing use, putting the total ending stocks ft For the 2008 crop year, the worldwide production of corn is projected at 30.9 billion bushels, up 0.3 percent from last month. Besides the U.S., corn production estimates increased in the European Union by 1.7 percent. Projected corn production in Brazil and the former Soviet republics was lowered by 3.5 percent and 1.6 percent respectively. The Brazilian drop was attributed to lower corn plantings for the main summer corn crop, which is being planted currently. Worldwide soybean production is projected at 8.8 billion bushels, up 0.6 percent from last month. The vast majority of the increase is due to the U.S. There were small increases in projected soybean production for the European Union and Canada. Production for Argentina, Brazil, and China were held unchanged. ra Reports out of South America indicate the combination of higher input costs and lower crop prices may hamper crop production growth there. Estimates from the Brazilian National Commodities Supply Corporation put Brazilian soybean area at 21.5 to 21.9 million hectares (53 to 54 million acres). USDA had released an earlier estimate of 22 million hectares. The Agriculture Secretariat of Argentina has projected soybean planted area of roughly 18 million hectares (44.5 million acres), up nearly 10 percent. Drought conditions and rising costs were seen as factor leading producers away from corn and wheat and to soybean. And officials in Paraguay expect soybean acreage to be in line with last year’s level. Crop demand On the demand side, corn feed demand is projected at 5.3 billion bushels, up 100 million from September, partially reversing an earlier downward adjustment. Lower corn prices are seen as the major reason for this shift. Corn demand from ethanol is projected at 4 billion bushels, up 1 billion bushels from last year. The ethanol industry has continued to grow, but the pace of growth has slowed. Lower corn prices imply lower production costs for ethanol plants, but plants are also seeing lower ethanol prices as U.S. consumers have reduced their fuel demand. Corn exports are projected at 1.95 billion bushels, down 50 million from September and down 485 million from last year. As Figure 3 shows, corn exports and outstanding sales are off of last year’s pace, but they are comparable to the pattern for 2006. With total corn usage estimated at 12.585 million bushels, the corn stocks-to-use ratio for 2008 stands at 8.6 percent, well down from 12.7 percent in 2007. d d ra ft World crop supply 50% 45% 45% 40% 40% 35% 35% 30% 30% 25% 25% 20% 20% ft 50% 10% 0% ra 5% 9/4 9/11 9/18 9/25 10/2 10/9 15% 10% 5% 0% 10/16 Week 2006 2007 9/4 9/11 9/18 9/25 ra 15% 2008 Integrated Crop Management Conference - Iowa State University — 85 ft 84 — 2008 Integrated Crop Management Conference - Iowa State University 10/2 10/9 10/16 Week 2008 2006 2007 2008 Soybean crush demand is estimated at 1.76 billion bushels, off 41 million bushels from 2007. Export demand is also lower than last year, at 1.02 billion bushels. However, export pace has been brisk, exceeding what we have seen over the past couple of years. In the mid-September USDA reports, soybean stocks-to-use ratios for 2007 and 2008 were below 5 percent. In these latest reports, those ratios were raised to 6.7 percent for 2007 and 7 percent for 2008. So the soybean stock situation remains tight, but not nearly as tight as it previously looked. The corn and soybean markets, like many commodity and stock markets, have taken a pounding over the last couple of months. Concerns about the general economy both here in the U.S. and worldwide have weighed heavily on market trading and have been a significant factor to the slide in crop prices. USDA significantly updated its season-average prices for corn and soybeans since September to $4.75 per bushel for corn and $10.45 per bushel for soybeans. The corn price is off 75 cents per bushel, while the soybean price is down $1.90 per bushel from September’s estimates. Futures prices point to stronger crop prices as we move toward next spring and summer. Basis levels for both crops have moved back toward historical averages. The combination of these price movements implies the potential for better crop returns for farmers who maintain ownership of their crops later in the marketing year. d Figure 4. The Pace of Soybean Exports (percentage of total marketing year exports and sales) d Figure 3. The Pace of Corn Exports (percentage of total marketing year exports and sales) Factors outside of agriculture will continue to strongly influence agricultural prices. The financial market turmoil is the dominant factor across many markets. Crop agriculture over the past couple of years has enjoyed strong demand for food, feed, and fuel use. But the concerns about the general economy lead to concerns about future crop demands both here and abroad. As Figure 5 shows, the outlook for overall fuel demand has dropped significantly over the past few months. Credit markets have tightened and, in some cases, ceased to function. Much of the funding for agricultural production and trade worldwide depends on liquid credit markets. 86 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 87 16 Add’l advanced Biodiesel Cellulosic 14 Feb The Outlook for 2009 d Many of the storylines for the crop markets in 2008 will continue in 2009. Tight stocks and strong demands for corn and soybeans will provide reasons for another healthy competition for acreage this coming spring. The ethanol industry will continue to grow as additional plants are finished out. These plants will be needed to meet the Renewable Fuels Standard targets over the next couple of years. Figure 6 displays the Renewable Fuels Standard targets for 2009-2011. As the graph shows, 10.5 billion gallons of conventional biofuels (mainly corn-grain-based ethanol) and 500 million gallons of biodiesel will be needed in 2009. Those amounts of biofuels translate into 3.75 billion bushels of corn and 345 million bushels of soybeans. Energy prices and the outlook for the general economy will strongly influence crop prices. And market volatilities will remain high as agriculture’s linkage to the energy markets grows stronger. Input costs had increased dramatically in 2008. And while diesel prices and some wholesale prices for fertilizer have begun to decline, that decline may not work in to Iowa farm costs until later in 2009. So while Iowa crop prices are likely to remain historically high, production costs will also reach historical highs. Crop margins will be much tighter than we have seen over the past couple of years. 8 6 4 2 0 2009 Additional Advanced Biofuels Cellulosic Biofuels Figure 6. Renewable Fuels Standard Targets ft ra Figure 5. Blended Motor Gasoline Consumption in the U.S. Source: U.S. Department of Energy, Energy Information Administration 10 2010 2011 Biodiesel Conventional Biofuels ra Oct ft Actual Conventional d Sept Billion gallons 12 88 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 89 Food and fuel: Enough grain but not enough processing Charles R. Hurburgh, Jr., Professor, Agricultural and Biosystems Engineering, Iowa State University John D. Lawrence, Professor, Economics, Iowa State University Raj. Raman, Associate Professor, Agricultural and Biosystems Engineering, Iowa State University ft The rapidly emerging renewable-energy industry has generated a lot of excitement in rural America. Ethanol plants, biodiesel refineries and wind farms are sprouting up across the Midwest as fast as investment bankers and pipe fitters will allow. The people who build and operate these renewable-energy facilities are welcome additions to many rural communities. These renewable-energy sources are land based. Farmers and rural communities are now as attuned to the Energy Bill as the Farm Bill. ra However, biofuels have also generated great controversy inside and outside agriculture. In some cases, traditionally allied agricultural interests – livestock and grains – have found themselves publically on opposite sides of policy issues. In general the discussion focuses on the new grain demand generated by biofuels, and whether that demand will outstrip or overbid supply to food uses. A few years ago, grain surpluses were driving prices to historically low levels in real terms, and government programs were contributing 50 percent or more to grain producers’ net income. Grain prices have tripled since 2005 and additional income is flowing into rural communities. Land prices increased 20 percent in the last year, setting record highs in most states and generating new wealth for landowners. Land rents also have risen, with increases of 25 to 40 percent commonly reported – a larger expense for renters, but more annual income for the owner. Economic shifts such as this create opportunities and challenges as they happen. d d ra ft Connie L. Hardy, Extension Specialist, Value Added Agriculture Program, Iowa State University Opportunities Biofuels have created several clear benefits in addition to new demand for grain and oilseeds. Some biofuels, such as biodiesel, reduce overall carbon dioxide emissions compared to petroleum. The cost of biofuels continues to drop in comparison to petroleum resulting in lower motor fuel prices for U.S. consumers. Biofuels have spurred investment in rural communities. First-generation biofuels, corn ethanol and soy biodiesel, have demonstrated the feasibility of large-scale biorefining, which has created investment in second generation technology. Farm receipts increased over a billion dollars in Iowa alone on higher crop prices. Equipment sales, housing, building construction and other services have increased sharply. The additional income from crop prices, bioeconomy investments and new employment has spurred economic activity in rural areas. 90 — 2008 Integrated Crop Management Conference - Iowa State University These gains have come with uneven distribution of benefits and higher risk to producers. Input costs rise to meet revenue with less “safety net” but there is much more income on which to make decisions. This demand driven market represents a reversal of the protected but mediocre income of previous farm programs. The acceptance of additional risk necessary to participate in the potential reward may be difficult. The safety net provisions of the Farm Bill are less relevant today. Previous decision making criteria based on farm programs may not work in the new more volatile market. 2008 Integrated Crop Management Conference - Iowa State University — 91 World Harvested Crops: Thousand Hectares Harvested 300,000 250,000 200,000 150,000 Challenges 100,000 0 00/01 World production in food, feed and fiber crops has also increased (Figure1). Between 2000 and 2008 crop years, harvested area increased 10.6 percent including 2.5 percent from 2007 to 2008. Yields have also increased and combined with acreage to grow production. Wheat and oilseed yields improved approximately 5 percent; course grains more than 10 percent; and cotton 25 percent (Figure 2). The higher prices since 2006 should encourage farms around the world to bring more land into production and to farm existing land more intensively. Technologies such as irrigation, fertilizer, and improved varieties make economic sense even to subsistence farmers as prices increase. 03/04 04/05 Course Grain 05/06 06/07 Oilseed 07/08 08/09 Cotton Percentage Change in World Production and Yields 07/08 v. 00/01 Crop Years ra 35% 30% 25% 20% 15% d d Given the opportunities and challenges of a growing biofuel sector, what might we expect of the future? The higher prices have brought more land acreage into production of carbohydrate crops. U.S. corn acreage increased by nearly 15 million acres in 2007 from 2006 and was the highest since 1944. During 2006 and 2007, sorghum, wheat, barley and oats added 7 million acres. Soybeans and cotton lost acres in 2007, but regained acres in 2008. 02/03 Figure 1. The marketing infrastructure is also adjusting to higher commodity prices. Processors often pass on feedstock price increases as percentage markups. A small change in feedstock price, around 20 percent, creates large increases at the supermarket. While higher energy prices have added to processing and distribution costs, a constant percentage markup on commodity prices that have doubled or tripled may not be warranted. Where to from here? 01/02 Wheat ra While some would draw a cause and effect linkage between ethanol and higher food prices, the actual linkage is weak at best as is discussed in another article in this series, Factors that Determine the Cost of Food. For example, livestock and poultry feed is the largest single user of U.S. corn but Jan. to July retail beef and pork prices increased 1.5 percent while retail chicken and turkey prices rose 6.5 percent. Feed costs have increased to producers of meat, milk and eggs, but through mid-2008 the supply of these commodities was still increasing suggesting that something other than a cost-induced reduction in supply is influencing these prices. One of those factors is exports; the rest of the world saw U.S. prices for these products as a value. In particular, dairy, poultry and pork exports have increased significantly in 2008. 50,000 ft ft Beyond the farm gate, a topic getting a lot of media attention is the impact of rising grain prices on consumer food prices. Food prices in the U.S. are increasing faster than the general rate of inflation, and faster than the 2.5 percent rate of recent years. 10% 5% 0% Wheat Course Grain Production Oilseed Cotton Yield Figure 2. With the present ethanol plants in operation or under construction, approximately 70 percent of Iowa corn will be processed for ethanol by 2010. This percentage could rise if additional plants now in various stages of planning are actually built. About one-third of the corn weight remains 92 — 2008 Integrated Crop Management Conference - Iowa State University acreage has shifted from year to year between corn and soybeans, but it hasn’t changed the supply of nutrients as much as the acreage may suggest. Soybeans are more highly concentrated in oil, protein, and essential amino acids than corn, in about the same ratio as corn but corn has higher yield per acre than soybeans. The acreage shift does not greatly affect total available nutrient supply (Table 1). Table 1. Nutrient unit production potential from Iowa corn and soybeans from the 2006 and 2007 crops. soybean d ------- million acres ------- DDGS SBM proten oil lysine ------------------------------- million tons ------------------------------- 2006 12.35 10.10 17.4 11.3 9.9 4.90 0.57 2007 13.85 8.52 20.8 9.8 10.1 4.85 0.54 The trade-off between feed and fuel issue may be more one of distribution and processing rather than a total quantity shortage. Processers and end users continue to adjust to the new supply and demand conditions. Farmers are also adjusting to the new costs and returns in the bioeconomy. Higher prices and revenue will encourage adoption of yield increasing technologies that were not practical at lower crop prices. As yields increase, a much greater supply of nutrient components not used by biofuel production could become available (Table 2). Animal nutritionists are rapidly developing diets that rely less on corn starch and more on non-fuel components. Protein (lb/A) Oil (lb/A) Lysine (lb/A) Fuel (gal/A) 150 630 302 21 420 250 1050 504 35 700 50 1050 555 83 56 80 1680 888 133 89 corn soybean New demand for corn and soybeans driven by biofuels is expected to bring more land into production and increase yields on existing land. In addition to larger supplies of grain and oilseeds, larger supplies of components of the crop not used for fuel will be available, relieving some pressure on feed and food prices. Challenges remain ft ra ft Technology and policy are pursuing biofuels beyond ethanol. Soy biodiesel is one example. In soybeans the situation is similar, except that biodiesel uses only the oil, approximately 20 percent by weight of the soybeans. Soybean processing plants extract the oil by either solvent or expeller press operations. The resulting co-product with soybean oil is soybean meal, a high protein feedstuff for livestock. Soybean oil is also a food product which had markets before the biodiesel developments. Iowa plants can crush essentially all the soybeans grown in Iowa. The biodiesel plants already on line or under construction could consume 72 percent of the soybean oil produced in Iowa. Announced plans for additional plants, if realized, would more than double the capacity testing the supply of soybeans at a time of increased competition for acres from corn. Yield (bu/A) Biofuels are part of a comprehensive energy program. Biomaterials are not a total replacement for all petroleum. The entire U.S. corn crop could only replace 10 to12 percent of gasoline usage. Bringing more land into production and using more intensive farming practices will present challenges that must be addressed. Biofuels are not a replacement for conservation, planning, and a total system energy strategy. The large-scale cultivation of dedicated biofuel crops may lead to significant environmental damages if not done properly. Implementation of best management practices to protect soil and water from erosion and nutrient runoff or leaching is necessary, but much of the science to create these practices is known. ra At the anticipated level of ethanol processing, recovering feed coproducts to the same utilization flexibility as the original corn could maintain animal nutrient needs. Germ protein, created by the fractionation process is higher in essential amino acids than corn protein as a whole, which means that fractionation could potentially create corn products more applicable to swine and poultry than the present distillers grains. Table 2. Impact of yield on grain component production per acre While the current biofuel explosion has focused on corn-based ethanol and biodiesel, the promise and policy is pointed toward cellulosic feedstocks for biofuels. These include crop aftermath, such as cornstalks and wheat straw, perennials like switchgrass and forestry products, and a new generation of energy crops. The goal is to utilize biomass feedstocks for fuel that do not compete with food. Currently, cellulosic ethanol production is technically possible, but it is not commercially feasible, and that is before the harvest, transport and storage of biomass is taken into consideration. Even when those hurdles are crossed, land-based feedstocks will still compete with food commodities for acres. d for animal feed after ethanol production. The growing opportunity is to modify the process by fractionation so that protein, oil and fiber streams of value are created for poultry and swine in addition to cattle feed. corn 2008 Integrated Crop Management Conference - Iowa State University — 93 It is important to recognize that while Iowa and the U.S. are leaders in the emerging bioeconomy, biofuel production is in it infancy. Ethanol production has increased rapidly as has grain prices. As producers and consumers adjust to the new market conditions and evolving technologies prices will also adjust. The transition will not be without challenges, but Iowa is well positioned to capture the opportunities in the years ahead. 94 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 95 Factors that determine the cost of food Chad Hart, Assistant Professor, Economics, Iowa State University John Lawrence, Professor, Economics, Iowa State University ft Iowa has moved to the forefront amid the shift to biorenewable sources of energy. The state is currently the leading producer of ethanol and one of the top producers in wind energy. As Iowa’s leaders, entrepreneurs, policy makers and researchers look to accelerate development of the state’s biorenewable resources, other impacts emerge. Today we are making choices about our economic, environmental, and social development as well as hurdling technical issues. The recent increase in the utilization of the state’s biological bounty for feed, food, and fuel has affected the economic, environmental, and social dynamics of Iowa. Global fuel, commodity, and food prices have increased substantially, particularly in the past two years. Media outlets have keyed on the food price increases as a negative and deflected blame onto growth in the biofuels industry. But there are a number of factors contributing to food cost increases. The U.S. food marketing system is a complex system linking farms to food consumers through a number of different entities. ra Most food products in the U.S. pass through layers of food manufacturing, distribution, wholesale, and retail companies. Each layer within the food marketing system has its own associated costs of doing business. Food prices reflect the sum of these costs. To form a basis for comparison on food cost impacts, economists often look at what is referred to as the food dollar, a breakdown of the average costs embedded in an average dollar spent on food. This paper will outline the factors that make up the food dollar and examine how those factors have changed over the past few years and have impacted food costs in the U.S. Current situation The U.S. food marketing system is made of five distinct sectors: agricultural production, food processing and manufacturing, wholesale distribution, retail distribution, and consumption. The middle three sectors link the farm to the food consumer and transform the basic agricultural commodities produced on the farm into the food products demanded by consumers. Based on U.S. Department of Agriculture (USDA) definitions, there are over 2 million farms across the United States. Production from these farms is purchased and processed by over 25,000 food and beverage companies. These companies, in turn, sell their production to nearly 33,000 food wholesalers, 113,000 food retailers, and 378,000 foodservice companies. The food products are then sold and distributed to over 111 million households throughout the U.S. In 2001, government estimates showed that 23.7 million people were employed in the food marketing system, with the largest number employed in food service, and that the food marketing system made up over 12 percent of the nation’s gross domestic product. These numbers indicate the vast contribution that the food marketing system makes to the overall U.S. economy in employment and value. d d ra ft Introduction 96 — 2008 Integrated Crop Management Conference - Iowa State University 45% 40% 35% ft 30% 25% 20% 19 50 19 54 19 58 19 62 19 66 19 70 19 74 19 78 19 82 19 86 19 90 19 94 19 98 20 02 20 06 15% ra Other Costs Business Taxes Interest Repairs Rent Depreciation Advertising ft Profits Energy Transportation Packaging a higher price due to increased preparation and packaging. This also implies that away-fromhome foods have a lower farm value percentage in the food dollar. Figure 2. Farm value share of the food dollar. Source: USDA-Economic Research Service 3.5¢ 3.5¢ 2.5¢ 1.5¢ 4¢ 3.5¢ 4¢ 4.5¢ 3.5¢ 4¢ 8¢ Examining the food dollar for individual foods Marketing Bill Figure 1. Components of the food dollar in 2006. Source: USDA-Economic Research Service A historical perspective on the food dollar The composition of the food dollar has changed dramatically over the last half-century. Figure 2 shows how the farm value in the food dollar has moved since 1950. In the early 1950s, over 40 percent of the food dollar was used to purchase agricultural products off the farm, in part because there was less processing, packaging, and preparation before the food reached the consumer. Since then, the farm value in the food dollar has declined to below 20 percent. Much of this change was driven by changes in U.S. eating patterns. In the 1950s roughly one-quarter of all food was purchased and consumed away from home (restaurants, cafes, etc.). That has risen to nearly 50 percent today. Food purchased and consumed away from home often carries The food dollar is also not constant across food products. Over the years, USDA has tracked the farm share in individual food items. Table 1 contains the 1998-2000 farm shares for various food products (this is the latest available from USDA for individual food items). As the table shows, the farm value varies sizably across foods. For dairy products, the typical farm value is between 30 and 40 percent. For fruits and vegetables, the farm value can range from below 10 percent to nearly 40 percent. For prepared foods, the range of farm values runs from less than 5 percent for bread and corn flakes to 25 percent for peanut butter. The farm values for meat products are approximately the same as for dairy products. Averaging over the 1998 to 2000 time period, farm values for pork were around 30 percent, while farm values for beef were nearly 50 percent. For 2006, USDA has released some farm value shares for food groups. The farm value share for cereals and bakery products is 6 percent; for fats and oils, it’s 16 percent; and for dairy products, it’s 27 percent. The farm value shares for fruits and vegetables are 16 percent for processing fruits and vegetables, 25 percent for fresh vegetables, and 30 percent for fresh fruits. d Farm Value 38.5¢ d 19¢ ra Labor The cost of food is based on the costs at each stage in the marketing system. One way to compare the various costs that make up food prices is to examine the food dollar, a breakdown of what a dollar spent on food actually pays for. The U.S. Department of Agriculture (USDA) tracks the costs in food. Figure 1 shows the latest food dollar estimate, based on 2006 data. The food dollar incorporates both food consumed at home and food consumed away from home (at restaurants, cafes, etc.) and divides costs into several major categories. On average, 19 cents of each dollar spent on food is used to purchase farm production. The other 81 cents covers the transformation of the farm production into the food products we purchase at grocery stores and restaurants. Labor costs are the largest component of the food dollar, making up nearly 39 cents. This is not surprising given the number of people employed in the food marketing system. Food packaging comprises 8 cents of the food dollar. USDA has computed that nearly half of all packaging materials in the U.S. are used by food processing and distribution companies. Transportation and energy account for 7.5 cents. 2008 Integrated Crop Management Conference - Iowa State University — 97 98 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 99 Corn syrup, 16-oz. bottle 3 3 3 Computed from unrounded farm values. Source: Calculated by ERS based on data from government and private sources. 1 Table 1. Farm share for individual foods Discussion 1999 2000 --------------- (Percent) --------------Dairy products: 41 39 34 Cheese, natural cheddar, 1 lb. 39 32 29 Fruit and vegetables: Frozen— Orange juice conc., 12 fl. oz. ft Milk, ½ gal. 38 37 33 11 10 12 8 8 7 Corn, 303 can (17 oz.) 23 22 22 Applesauce, 25-oz. jar 14 14 16 Apple juice, 64-oz. bottle 32 19 18 Green beans, cut, 303 can 14 13 13 Tomatoes, whole, 303 can 7 7 7 Beans, 1 lb. 20 20 19 Raisins, 15-oz. box 29 36 16 Sugar, 1 lb. 32 31 27 Flour, wheat, 5 lbs. 20 18 19 Margarine, 1 lb. 26 17 15 Rice, long grain, 1 lb. 22 19 14 Peanut butter, 1 lb. 26 23 22 Pork and beans, 303 can (16 oz.) 11 11 11 Potato chips, regular, 1-lb. bag 8 9 8 Chicken dinner, fried, frozen, 11 oz. 13 13 14 Potatoes, french fried, frozen, 1 lb. 11 11 10 Bread, 1 lb. 5 5 5 Corn flakes, 18-oz. box 4 4 4 Oatmeal regular, 42-oz. box 6 5 5 Broccoli, cut, 1 lb. Corn, 1 lb. ra Canned and bottled— Dried— d Crop products: Prepared foods: As the above discussion highlights, the food dollar continues to evolve with our eating patterns and changes in food technology. The general linkage between farm and food prices has declined dramatically over the last half-century. Farm values in food prices tend to be the highest for meat and dairy products or for food products with minimal processing. Processing, packaging, transportation, and advertising costs for our foods now make up a substantial portion of the food dollar. And these costs will continue to grow in importance as we continue to shift to consuming more foods away from home or more highly processed or prepared foods at home. Over the past few years, fuel, food, and commodity prices have risen and U.S. consumers have felt the impacts on the family budget. Typically, food prices increase by 2.5 percent per year. Table 2 displays the percent changes in consumer price indexes for food from 2005 to 2009. And while the U.S. experienced typical food price inflation in 2005 and 2006, the rate of food price increases has picked up in 2007 and is projected to remain higher than normal for 2008 and 2009. Higher commodity prices for corn, soybeans, and wheat, driven by crop demands for feed, food, and fuel, have contributed to this increase. Corn and soybean prices have more than doubled since September 2006, but food prices have on average increased by 4 percent during 2007. While food prices do react to commodity prices, as the farm value data shows, the reaction is fairly small. On average, 80 percent of food prices are covering costs beyond the farm gate. Energy and labor costs make up the largest portions of these additional costs. Crude oil prices were between $55 and $60 per barrel at the beginning of 2007 and they are well over $100 per barrel today, after peaking above $145 per barrel earlier this year. As crude oil enters the food marketing system in several ways (diesel fuel to power the tractors on the farm and semis across the country, plastic to package foods), its price increases also impact food costs. ft 1998 ra Food As the table shows, food costs are expected to increase by 4 to 5.5 percent both this year and next. The price increases range across all types of foods. For 2008, eggs, fats and oils, and bakery products will likely see the highest increases. For 2009, meat and dairy product prices are projected to increase the most. Some of the price support for the meat and dairy sectors is coming from stronger export demand for pork and dairy. While biofuel production can be pointed to as a possible reason in some categories (meats, dairy, bakery), it has minimal impact on others (fruits and vegetables). The prevalence of crude oil in the food marketing system implies that higher energy costs are also a driving factor in the projected food price increases. d Farm share of retail price1 Summary U.S. consumers have been facing higher fuel, commodity, and food prices over the past couple of years. The growth of the biofuels industry has coincided with these challenging cost trends making it easy for pundits and analysts to argue cause and effect. The biofuels industry is a significant new end user of commodities which certainly has an effect on supply and demand relationships, but there are a number of other factors that have influenced food prices as well. The increase in crude oil prices not only pushes food prices higher, but also has provided incentives for the biofuel expansion. To understand all of the various forces that affect food BLS estimated expenditure shares, December 2007. Forecasts updated October 20, 2008. Source of historical data: Bureau of Labor Statistics Forecasts by USDA-Economic Research Service. 2 1 55.4 12.2 7.9 3.8 2.4 1.7 2.3 2.0 0.9 6.4 1.5 8.4 6.6 3.4 3.2 1.8 2.0 7.4 6.7 9.9 1.9 2.4 2.3 2.6 2.0 2.4 2.0 3.0 -13.7 1.2 -0.1 3.7 3.9 3.7 4.0 3.3 1.2 1.5 2.9 1.6 4.2 3.8 3.3 4.4 2.0 2.3 5.2 4.6 29.2 7.4 2.9 3.8 3.9 4.5 3.2 3.6 3.1 4.4 4.1 1.8 3.6 5.5 to 6.5 3.0 to 4.0 2.0 to 3.0 3.0 to 4.0 1.5 to 2.5 1.0 to 2.0 4.0 to 5.0 5.5 to 6.5 13.5 to 14.5 8.0 to 9.0 13.0 to 14.0 6.5 to 7.5 6.0 to 7.0 6.0 to 7.0 6.0 to 7.0 8.5 to 9.5 4.5 to 5.5 9.0 to 10.0 3.5 to 4.5 4.0 to 5.0 3.5 to 4.5 5.0 to 6.0 (Percent change) 4.0 ft 1.7 0.8 0.7 0.8 -0.2 1.8 -1.8 4.7 4.9 -0.6 0.2 4.8 5.3 6.0 4.6 2.9 3.8 1.8 2.0 1.4 3.1 Forecast 20082 Final 2007 4.0 to 5.0 5.0 to 6.0 5.5 to 6.5 6.0 to 7.0 5.0 to 6.0 2.5 to 3.5 5.0 to 6.0 4.0 to 5.0 1.0 to 2.0 4.0 to 5.0 3.0 to 4.0 3.5 to 4.5 4.0 to 5.0 4.0 to 5.0 3.5 to 4.5 3.0 to 4.0 3.0 to 4.0 3.5 to 4.5 3.0 to 4.0 3.0 to 4.0 4.0 to 5.0 4.0 to 5.0 Forecast 20092 Food at home Meats, poultry, and fish Meats Beef and Veal Pork Other meats Poultry Fish and seafood Eggs Dairy products Fats and oils Fruits and vegetables Fresh fruits & vegetables Fresh fruits Fresh vegetables Processed fruits & vegetables Sugar and sweets Cereals and bakery products Nonalcoholic beverages Other foods 3.1 2.4 2.4 Final 2006 ra 44.6 Food away from home All food Final 2005 ft Values at the farm level make up less than 20 percent of food costs. This means that 80 percent of the cost of food is due to events beyond the farm gate. And while biofuel production has been one of the major reasons for higher commodity prices, it has little impact on food costs beyond the farm. Higher energy prices and general economic conditions also have impacts on food costs at and beyond the farm. Relative importance1 (Percent) 100.0 ra prices, we must examine the U.S. food marketing system and explore the numerous costs that must be covered by our food dollars. Consumer price indexes Table 2. Changes in food price indexes, 2005 - 2009 d d 100 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 101 102 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 103 ACRE and Sure: Two new commodity programs under the 2008 Farm Bill William Edwards, Professor, Economics, Iowa State University ft Federal disaster payments for areas that have suffered severe crop losses have been around for a long time. However, they have usually been implemented on an ad hoc basis each time widespread productions problems arose. The new farm bill changes this. In addition, producers of USDA program crops such as soybeans, wheat and corn have the option to enroll in a new counter-cyclical revenue plan. It is being offered as an alternative to the price counter-cyclical payment option under the 2003 farm bill. Supplemental Revenue Assistance ra The 2008 farm bill, officially known as the Food, Conservation and Energy act of 2008, creates an Agricultural Disaster Trust Fund. A major part of this fund will finance Supplemental Revenue Assistance (SURE) payments, which are designed to supplement the protection producers can purchase from private crop insurance companies. In fact, a producer must purchase insurance for all crops produced each year to be eligible for the SURE disaster program, starting in 2008. Farmers who have land in a county that has been declared a “secretarial designated” disaster county, or land in a county that is contiguous to a disaster county, may be eligible to receive a SURE payment. Farming operations not in eligible counties could also qualify if they have more than a 50 percent loss in the value of their crop production due to weather related causes. In addition, at least one crop on the farm must suffer a yield loss of ten percent or more for the farm to receive a payment. SURE is a revenue guarantee program, similar to crop revenue insurance without the increasing guarantee feature. If the farm’s actual crop revenue is less than the guarantee, the SURE payment makes up 60 percent of the difference. The actual crop revenue includes not only the estimated value of the crop produced, but also other USDA payments and crop insurance indemnity payments received. This prevents farmers from receiving double payments for the same losses. All guarantees and actual revenues under SURE are calculated as the sum for all crops and in all counties involved in the “farming operation”, even if land in more than one county or state is involved. Payments are not made for losses to individual crops or insurance units. d d ra ft Introduction The guarantee The SURE guarantee is simply the sum of all the crop insurance guarantees purchased for the current crop year, increased by 15 percent. The extra 15 percent is designed to fill part of the revenue gap not covered by insurance. For example, a producer who purchased a 75 percent guarantee on all crops would have that raised to 86.25 percent for SURE. There is also an overall “cap” on the SURE guarantee equivalent to a 90 percent insurance guarantee on all crops. If the crop insurance proven yield (APH yield) is less than the yield used by the Farm Service Agency to calculate counter cyclical payments (CCPs), then the CCP yield is used instead for calculating the SURE guarantee. Producers who have used “plug” yields to calculate their APH yields in some low production years will also have their SURE yield recalculated. Actual revenue ft The SURE “actual revenue” includes the actual number of bushels harvested for each crop valued at the average cash marketing year price as determined by the USDA. For corn and soybeans this price is calculated from September through August, so the actual revenue and payments for 2008 crops will not be known until September 2009. Advance payments could be authorized, but this has not been announced. The cash marketing year price may be higher or lower than the harvest futures price used to calculate crop insurance indemnity payments. Table 1. Supplemental Revenue Assistance (SURE) Example Corn Planted acres 160 bu. 50 bu. Crop insurance indemnity price $5.40 $13.36 Crop insurance guarantee level 75 % 75 % $324,000 $250,500 500 acres 500 acres 150 bu. 42 bu. 75,000 bu. 15,000 bu. $4.00 $10.00 $300,000 $210,000 $510,000 $24,000 $40,500 $64,500 APH crop insurance yield Crop insurance revenue guarantee (acres x yield x price x % guarantee)* Harvested acres Harvested yield actual bushels harvested Crop insurance indemnity payment Stay in touch with your local FSA office for more details on SURE. Crop insurance indemnity payment (insurance guarantee less actual revenue)* SURE guarantee (115 % of insurance guarantee)* Marketing year average cash price actual revenue for SURE (bu. x market yr. price) ra d The maximum CAT charge is $900 and the maximum NAP charge is $750 per producer per county. After 2008 all crops must be insured by the sales closing date, which is March 15 for most Iowa crops. Fall seeded crops such as hay and winter wheat have a September 30 deadline for CAT or “buy-up” insurance, and a December 1 deadline for NAP. actual revenue for crop insurance (bu. x price) $3.75 $9.50 $281,250 $199,500 15 % of USDA direct payment ($20,000) 1,000 acres $574,500 $660,675 $480,750 $64,500 $3,000 Total crop revenue for SURE $548,250 Revenue shortfall for SURE (guarantee less actual) $112,425 SURE payment (60 % of shortfall) $67,455 *Assumes basic revenue insurance. For CRC or RA-HPO the final guarantee could be higher since the harvest price exceeded the initial indemnity price. Average Crop Revenue Election d ra If the actual revenue calculation is below the SURE guarantee, the producer will be paid 60 percent of the difference. There is a limit of $100,000 per year per eligible producer, based on the same rules outlined for other commodity programs in the new farm bill. Crops not eligible for private insurance but which are eligible for the Noninsured Assistance Program (NAP) offered through FSA also need to be covered. These include many horticultural crops and some forage crops, but not pasture. The NAP fee is $250 per crop. Beyond insuring all crops, no other signup is necessary to be eligible for SURE. Total 500 acres Harvest time insurance price To be eligible for SURE payments a producer must insure all of his/her eligible crops.. Approximately 90 of the corn and soybeans in Iowa are covered by crop insurance each year. However, only a small percent of other crops such as oats, wheat and hay are typically insured. Even a small patch of hay that is not insured can cancel eligibility for SURE payments on all the acres of corn and soybeans on the same farm. Soybeans 500 acres In addition, the actual revenue includes any crop insurance indemnity payments and prevented planting payments received for the 2008 crop, and 15 percent of any direct payments, counter cyclical payments and loan deficiency payments received for the 2008 crop. Unless corn and soybean prices drop considerably in the next year, the direct payments will be the only commodity program received for the 2008 crop. Starting in 2009 payments received under the ACRE program will be included, too. If payments are received under any other USDA crop disaster programs, these are also included. Insure all crops 2008 Integrated Crop Management Conference - Iowa State University — 105 ft 104 — 2008 Integrated Crop Management Conference - Iowa State University The current counter-cyclical payment (CCP) program becomes effective when the season average marketing price for a commodity is below the national target price for that commodity. There is a maximum payment level per bushel of program yield, and it is paid on 85 percent of the program base acres. Critics of the CCP have pointed out that it addresses price risk only, and not production risk, and it is not based on the crops or acres actually being grown by the producer each year. ACRE addresses both of these problems. ACRE guarantees ACRE uses a combination of state average yields, farm level yields, and the national marketing year price to determine levels of revenue guarantees and payments for each covered commodity. There are two revenue triggers that have to be met before any ACRE payments are generated, one at the state level and one at the farm level. Farms correspond to FSA units, just as for the current commodity programs. The price component of both of these is the average of the two ra Actual revenue ft The state revenue guarantee is 90 percent of the average state yield multiplied by the two-year average marketing price. For the farm level revenue guarantee, the same two-year average price is used, multiplied by the Olympic average of the last five years of yields for the farm. The value of the farmer paid crop insurance premiums is also added to the farm level guarantee. Both the state and farm guarantees will be recalculated each year using prices from the past two years and yields from the past five years. To trigger a payment under ACRE the “actual” revenue for both the state and the farm must be less than their corresponding guarantees. The actual revenues are the current marketing year price multiplied by the state average yield and the actual farm level yield, respectively. If both triggers are reached, the payment to the farm will be the difference between the state guarantee and the state actual revenue. The payment level cannot exceed 25 percent of the state guarantee, however. It will also be adjusted up or down by the ratio of the farm Olympic average yield to the state Olympic average yield. For example, if the farm average yield is 10 percent above the state average yield, the ACRE payment will be increased by 10 percent for that farm. d The payment will be made on 83.3 percent of the farm acres planted to the crop (85 percent in 2012). However, the planted acres that receive a payment cannot exceed the total base acres established for the counter-cyclical payments in the signup for the 2003 farm bill program. Producers who sign up for ACRE will continue to receive 80 percent of the direct payments that have been paid, regardless of actual prices or yields each year. How much does ACRE cost? Producers who sign up for ACRE will forfeit 20 percent of their current direct payments through 2012, so that is a fixed cost. They will also give up any potential counter-cyclical payments, and the loan rate used to calculate their loan deficiency payments or marketing loans will be lowered by 30 percent. The loss of potential CCPs and LDPs may not be too critical, because if market prices fall enough to trigger those payments it is likely that the ACRE payment would be at least as large. The only situation where that would not be true is a year in which prices were low but yields were high enough to keep revenue above the ACRE guarantees. ACRE does not replace crop insurance Although the ACRE program may resemble crop revenue insurance, there are some important differences. The ACRE guarantees are based on longer term average prices and yields, so they will not fluctuate as much from year to year as crop insurance guarantees. In fact, ACRE regulations state that the guarantees cannot increase nor decrease more than 10 percent each year. This helps accomplish the fundamental goal of ACRE, which is to stabilize gross revenues over the next 4 years. On the other hand, one of the two ACRE guarantees and the size of the payment are based on state level yields, not farm yields like most crop insurance policies. ACRE does not protect a farmer who has a poor production year when the state as a whole does not. In addition, ACRE revenue uses the marketing year cash price to calculate actual revenue while crop revenue insurance uses futures prices at harvest time. So, while ACRE payments can be a useful risk management tool for sharply falling prices or widespread yield losses, they do not replace farm level crop insurance protection. Should I sign up? ft For the state revenue guarantee, an “Olympic” average of the state average yields for the past five years is used. The highest and lowest values during this period are thrown out, and the values for the three remaining years are averaged. Average yields are adjusted to bushels per planted acre rather than per harvested acre. Based on the most recent USDA yield forecasts, the 20042008 Iowa average yields for ACRE will be about 166 bushels for corn and about 50 bushels for soybeans. 2008 Integrated Crop Management Conference - Iowa State University — 107 Producers can sign up for the ACRE program beginning in any crop year from 2009 through 2012. Once enrolled, they must remain in the program through 2012. All program crops on the farm must be enrolled. The decision of whether or not enroll is a classic insurance decision. Producers will give up a fixed amount of revenue, 20 percent of their direct payment, in exchange for a possible ACRE payment in a year when gross revenue is low. Payments could be zero in all four years, or they could be sizable. ra most recent USDA marketing year prices. For corn and soybeans the marketing year runs from September through August. Marketing year prices are based on cash prices (not futures) paid throughout the country. The marketing year prices for the 2007 crops are projected to be $4.00 for corn and $10.40 for soybeans. One key factor is the level of guarantee established for the 2009 crop. The 2008 marketing year price will not be known until September 2009. However, it seems likely that the beginning guarantees will quite high by historical standards, and they cannot decline by more than 10 percent each year afterward. This would make the ACRE program attractive, especially since target prices and loan rates are essentially frozen at the levels established in the 2003 farm bill. The other key factor is the likely price trend over the next four years. If production is stable and prices either trend upward or are steady, no ACRE payments are likely, and the producer will simply lose part of the direct payment. However, if prices trend downward from present levels, ACRE will provide an important safety net for gross revenues. Each individual producer will have to assess his or her expectations for the future and need for financial risk protection before making the ACRE decision. d 106 — 2008 Integrated Crop Management Conference - Iowa State University 108 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 109 Estimating costs of crop production for 2009 Table 2. Example of ACRE for corn in Iowa Assume the 5-year Iowa Olympic average yield is 166 bushels. Michael Duffy, Professor, Economics, Iowa State University Assume the 5-year farm Olympic average yield is 175 bushels. • 2009 farm level guarantee = (175 bu. x $4.50) + $20.00 = $807.50 Assume the actual 2009 state yield is 150 bushels per acre. ft Assume the actual 2009 farm yield is 160 bushels per acre. Assume the 2009 marketing year price is $4.00 per bushel. • 2009 actual state revenue = 150 bu. x $4.00 = $600.00 • 2009 actual farm revenue = 160 bu. x $4.00 = $640.00 Since both the state and farm actual revenues are below their guarantees, an ACRE payment is earned. • ACRE payment = ($672.30 - $600.00) x 83.3 % x (175 bu. / 166 bu.) = $63.49 per acre ra The difference between the state guarantee and the state actual revenue ($72.30) is paid on 83.3 percent of the planted acres, and is adjusted for the farm yield being higher than the state yield. References Edwards, William. 2008. SURE payment calculator. http://www.extension.iastate.edu/agdm/ crops/xls/a1-44surecalculator.xls d Zulauf, Carl. 2008. 2008 farm bill: With a focus on ACRE and SURE. http://aede.osu.edu/ resources/docs/pdf/SWZ52I3V-YNCP-EWGZ-VBNKBJMT9NMJM7C4.pdf Estimating costs of production for 2009 will be extremely difficult. Some farmers have received forwarding pricing, some set a quantity only and still others will use the spot market. The price consequences of these decisions are substantial. Foreign competition for material, the current U.S. financial crises, the energy price situation and a host of other factors compound estimation problems for Iowa farmers. In these times it is easy to simply say it can’t be done with any accuracy so why bother trying it. ft • 2009 state revenue guarantee = 90% x 166 bu. x $4.50 = $672.30 Introduction Such thoughts are understandable but it is precisely times of uncertainty when estimating the costs of production is the most crucial. Farmers need an estimate of costs for cash flow planning purposes. Credit markets have tightened considerably and working with a lender having a clear understanding of credit needs will aid in securing credit for 2009. Farmers need to know their costs of production when they establish their marketing plan. Based on USDA monthly price reports for Iowa, corn prices have dropped 22 percent from July through mid October and soybean prices have dropped 27 percent over the same time period. Farmers need to know their costs of production in such volatile times if they are going to be able to follow a sound marketing plan. The old saying is you won’t go broke locking in a profit but you do locking in a loss. Without knowing costs of production the farmer can’t tell. ra Assume the average crop insurance premium paid per acre is $20.00 Input markets for just about all inputs have soared as commodity prices increased. Farmers need to know their costs of production so they can tell where to concentrate for trimming costs of production. Too often in such times the strategy is simply cutting back but this can do more harm than good if cuts are made in the wrong area. Time should be spent concentrating on where costs are out of line rather than areas where costs are more reasonable with respect to averages. It is easy to say that costs can’t be estimated in this environment so why bother. But, this type of environment is exactly the time when estimates are crucial. d Assume the 2007-2008 average marketing year price is $4.50 per bushel. Estimated costs for 2009 Diesel fuel costs show considerable volatility. Current reported fuel prices are down 25 percent from just a month ago and down 28 percent from the highest reported. Yet, they are only down one percent from a year ago. Where the prices will go over the next several months is subject to debate. What isn’t debated too widely is that they will continue to trend upward. Farmers are well advised to continue to find ways to cut machinery costs. Evaluating trips, keeping power units tuned, and proper tire inflation are just some of the ways to reduce diesel use. Of course, when replacing machinery energy efficiency needs to be a consideration. Reported seed costs showed considerable variation this year. The biggest difference was the traits contained in the seed but even when comparing similar traits, reported seed prices varied widely Farmers need to carefully evaluate seed selection and planting rates. The standard evaluations for yield, standability, moisture at harvest and so forth are all still important. But, with the new traits and multiple stacks farmers need to carefully consider if the trait being offered is one they need or will benefit from having. ft Seeding rates are also important. Research reported in the Iowa State University ICM newsletter suggests that higher seeding rates more be advantageous in some cases. The maximum profit rule of using an input to the point of diminishing marginal return is very important to remember. Expected output prices and seed costs will determine the optimum seeding rates. Costs for fertilizers have soared in the past few years. Based on data from the Iowa Farm Business Association, fertilizer and lime costs per acre for corn have increased by 64 percent in just the past 5 years. Costs for 2008 and estimated costs for 2009 will be even higher. Estimating fertilizer costs has become increasingly difficult as prices change within the season and different payment regimes are initiated. ra World competition for plant nutrients has led to the increase in prices. So, too, has the increased concentration in the industry. With fewer manufactures prices are more closely tied to output prices. In addition, costs for storage can be pushed further down to the final user, increasing costs and changing terms of sale for farmers. Current prices are projected to remain steady for N and P but uncertain for K. There should be some reduction in prices as the lower priced material works its way into the world market and the higher priced material is sold. d Farmers need to follow sound agronomic practices as they assess their situation in the new environment. Proper soil tests are more important than ever. New tools are developed to help determine proper application rates with different input and output price combinations. Staying up-to-date with the latest agronomic recommendations is essential. Pest management is another area where costs have increased considerably. Projections for 2009 for at least one of the more popular herbicides are for almost a doubling in price. Data from the Iowa Farm Business Association shows that herbicide costs per acre for soybeans and corn have been flat to drifting downward. This appears to be over starting in 2009. Cash rent for 2009 is projected to be up but the amount of increase will vary considerably based on conditions and the quality of the land. Average rents are projected to increase by eight percent over 2008 levels but, again, this will vary considerably. Cash rents will follow land values. Land values, in turn, are dependant upon the income that can be earned. Decreased commodity prices and higher input costs will lower returns and should lead to lower rents. The average rent per acre has increased by almost 30 percent in the past 3 years. Farmers need to try and work with landlords to develop flexible leases. With rapidly rising and volatile costs and changing markets this is especially important. A landlord may want a fixed amount but be willing to share above that certain price. Flex features can be worked out between the tenant and landlord. Taking all these uncertainties into account the preliminary estimated costs of production of Iowa State University for continuous corn are $5.63, $5.30, and $5.03 per bushel. This assumes an average yield of 125, 145, and 165 bushels per acre, respectively. For the average yield, the 2009 estimated costs are 28 percent higher than last year for continuous corn. They are 73 percent higher than 5 years ago. The estimated costs of production per bushel for corn following soybeans are; $4.59, $4.42 and $4.30 assuming 140, 160, and 180 bushels per acre, respectively. These cost estimates are, for average yield, 27 percent higher than last year’s estimate and 72 percent higher than the 2004 estimated costs. Cost of production estimates, per bushel, for soybeans are; $10.41, $10.11 and $9.94 assuming 45, 50 and 55 bushels per acre. The average estimate is 29 percent higher than a year ago and 54 percent higher than the estimated costs 5 years ago. ft The seed industry continues to change. Concentration in the industry will reduce competition which will increase prices. But, the traits and combination of traits being offered seems to continue to increase almost exponentially. 2008 Integrated Crop Management Conference - Iowa State University — 111 For corn, land represents approximately 30 percent of the total costs of production. This assumed $178, $205, and $232 per acre rent charges for the low, medium and high quality land. The variable costs represent almost 60 percent of the costs of production. Of the variable costs, nitrogen and seed costs are almost half the costs for either continuous or rotated corn. Nitrogen was charged at $.75 per pound and seed was assumed to cost $250 per bag. ra depending upon the source. Differences of up to 30 percent were not uncommon. Land represents just over 40 percent of the costs of production for soybeans. While the variable costs represent 44 percent. Seed and potassium are almost half of the variable costs. Phosphorus was charged at $.94 per pound and potassium at $.75 per pound. Changing seed prices by 20 percent causes approximately a 3 percent change in the cost per bushel for corn. A 13 percent change in the price per pound of nitrogen causes a 2.5 percent and 2 percent change in the costs of production per bushel for continuous corn and rotated corn, respectively. If we assume that the cash rent charge did not change from last year, a 5 percent decrease in what was used for the average yield, then the costs of production per bushel would decrease by 1.9 percent, 2 percent and 3 percent for continuous corn, rotated corn, and soybeans, respectively. However, if we assume that rents increase by 21 percent from 2008s estimated average level, then costs per bushel would increase 5 percent 6 percent, and 8 percent for continuous corn, rotated corn, and soybeans, respectively. d 110 — 2008 Integrated Crop Management Conference - Iowa State University Conclusions Costs of production will be up considerably for Iowa farmers. By how much will depend on individual circumstances and the validity of the assumptions that need to be made. The average costs, per bushel, are estimated to be approximately 30 percent higher than last year. And, over 70 percent higher for corn and over 50 percent higher for soybeans, than the estimated costs just 5 years ago. Farmers need to be prepared for volatility in prices and commodity prices. Risk management is going to take on a new meaning and urgency in the years ahead. In some cases the wild 112 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 113 gyrations of the past few years will settle out but for the most part this will be at a higher level. For most of our inputs, however, fluctuations caused by increased world competition, increasing industry concentration, fluctuating energy costs and other factors will continue. Theory and practice of integrated pest management in the 21st century The recent energy related boom in for agriculture has faded. When and if it will return are being debated. But, one thing is clear, Iowa farmers have to start preparing for rapid fluctuations in input and output prices. Marlin E. Rice, Professor, Entomology, Iowa State University Introduction ft Webster defines a pest as any plant or animal that is detrimental to humans or human concerns (especially in agriculture or livestock production). Pest control has been a serious issue for humans since the dawn of civilization. Through the centuries, mechanical, biological, cultural and chemical controls of pests have evolved. The reasoned use of pesticides dates to at least 2500 BC, when sulfur was used as a control of mites and insects. As technology advanced, control measures were adjusted and new techniques and materials were discovered, and those changes greatly accelerated in the previous century. The evolution of pesticide use ra One marker of the dawn of the modern, artificially produced pesticide era is Paul Müeller’s 1939 discovery of DDT at the Geigy Chemical Company. During World War II, DDT found extensive and successful use in combating the insect vectors of yellow fever, malaria and typhus. About the same time, the chemical 2, 4-D was developed as a defoliator to assist clearing vegetation for battle targeting in the war. At the end of the war, attention shifted to peacetime uses of these and other chemical “tools” to protect against pests, with crop production being the major focus. These new chemicals rapidly gained overwhelming popularity. However, dark clouds gathered on the horizon associated with the growing dependence on pesticides for economic pest control, notably the early development of resistant pest lines, and environmental concerns when products applied for good purposes wound up leaving the site and causing non-target damage, or lasted long enough to carry over and cause problems in subsequent crops. In 1947, the Federal Insecticide, Fungicide and Rodenticide act (FIFRA) became law, establishing a regulatory framework for registering pesticide products and regulating their safe use in the United States. d d ra ft The outlook for 2009 isn’t especially bright currently. Commodity prices are down almost a fourth from recent highs and input costs are estimated to be almost the same percentage higher in 2009. It is easy to get discouraged and neglect sound business practices in such times. But, now is the time when we need to know our costs. Average estimates and estimates from other farms can be good guidelines but nothing substitutes from knowing our costs of production. Remember that over the past 40 years there as only been 1 year when the top third farms in the Iowa Farm Business association didn’t make money. Somebody is always making money in Iowa agriculture. Richard Pope, Extension Program Specialist, Plant Pathology and Entomology, Iowa State University In the late 1950s, researchers explored scientific-based strategies toward wise use of pesticides, including using economic appropriateness as a key to decision making about product use and rates. The concepts of economic injury levels and economic thresholds were developed and employed as agriculturalists learned to use pesticides more effectively. Economic injury levels (EILs) and economic thresholds (ETs) are derived by knowing what size pest population will cause sufficient damage to a crop that a practice or treatment will save at least the cost of treatment. These paired concepts are foundations of a management regime called Integrated Pest Management, or IPM. IPM encourages consideration of the use of different cropappropriate and pest-appropriate tactics, including cultural—such as crop rotation or variety selection, mechanical—such as cultivation, biological—including both controlled releases and consideration of practices to avoid the loss of biocontrol agents and finally chemical—including pesticides. By understanding the dynamics of when a given pest is damaging and when it should 114 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 115 years, understanding how ambient temperatures affect development of several insect pests (including black cutworm, bean leaf beetle, and stalk borer) of corn and soybean allows for more effective scouting and treatment. In 1962, further attitude change toward pest management was highlighted with the publication of Silent Spring by Rachel Carson. The central theme of the book is a wake-up call to society in general about adverse effects on ecosystems from pesticide use. As the 1960s turned into the 70s, the United States established the Environmental Protection Agency (EPA) as an administrative unit to oversee and regulate most societal practices that carry environmental consequences. Very early on, administration of most of the regulatory function of FIFRA and related laws was transferred to the EPA. The core principles of IPM were encouraged as a way to approach wiser use of pesticides, because accommodation of environmental concerns and avoidance of adverse environmental effects are included and are part of decision making at the farm level. Labor d IPM is a system that incorporates change as conditions warrant. That ability to adopt is important because a major factor in agriculture is change. Farms are industries that function by coordinated use of four major natural resources, namely land, climate, labor and genetic material. Each of these four resources has been and will continue to be a focus of change that affects management decisions. Notable examples for each include the following: Land Perhaps the most constant of the four inputs, but increased understanding of land capabilities allowed for more appropriate uses with increased productivity. Erosion control practices including waterway and terrace establishment, or more subtle practices like improved crop residue management. Climate Understanding predictable patterns has historically changed farming practices. In the early 1900s, Iowa wheat farmers learned that damage from a particularly devastating pest called the Hessian fly could be minimized by planting after the fall “fly-free” date, so wheat was emerging after the fall oviposition. Fly-free dates varied from south to north based on climate. In recent Pest Base (°F) Use of Degree Days (DD) 39 Adults emerge at about 200, 600 and 1000 DD Black cutworm 51* 300 DD from egglaying to cutting Stalk borer 41 Western bean cutworm 50 When 1,300-1,400 DD have occurred in an area, scout by pulling whorls to determine if larvae are present. 50% adult emergence and egglaying at 1422 DD after May 1 ft Seedcorn maggot *previously was 50°F but current research has established 51°F as more accurate. The shift from horse-driven implements to internal combustion engines permanently changed agriculture, allowing larger, faster equipment that could cover more acres in less time with fewer operators needed per acre.With fewer operators needed per acre, the number of farm units has dropped through time. ra Changes in agriculture Table 1. Examples of degree days for insect management on Iowa corn Genetic materials The introduction of hybrid corn to agriculture revolutionized agronomy in the Cornbelt. And this revolution has continued as plant breeders have discovered traits that have improved yield potential and afforded insect and disease tolerance and resistance. In the last two decades, access to technologies that allow insertion of new genetic material from other species into the genome have dramatically altered the crops we grow. Chief among these are Bt-resistance for insect management and herbicide resistance for weed management. These new technologies can provide great economic benefits but also present great challenges. As with any new advance, there are consequent peripheral considerations. Genetically engineered crops are viewed skeptically by some as a threat to natural ecosystems, and containment of the genetic from “escaping” the field is raised as a concern. But greater concerns lie in the widespread use of one of these transgenic tools. One is that widespread use may lead to the target pest potentially developing tolerance or resistance to that tool so it loses effectiveness. In addition, the blanket use of a transgenic crop (or some non-transgenic practices, for that matter) can lull the producer into a false sense of security. From the assumption that a transgenic crop is controlling a pest has sometimes led growers to reduce monitoring of weed or insect issues, reducing their ability to catch emerging problems early. d ra ft be controlled, these control tactics can be targeted most appropriately. Economic thresholds are important in that they anchor pest management decisions to an economic foundation—which is palatable to the grower who can see tangible benefits. But for some pest situations where research has not or cannot establish economic responses to base an ET, other reasonable action thresholds have been developed. These “nominal” thresholds are based upon a person’s understanding of the pest’s biology tied together with field experience, and are rarely based on rigorous research. Nominal thresholds tend to be static--that is, unchanging with changes in crop value, control costs, or plant development stage. As an example, the current threshold values used in Iowa for western bean cutworm management on corn are nominal thresholds. Although western bean cutworm has been reported in Iowa for decades, economically damaging populations were only observed, starting in the early 2000s. These nominal thresholds were applied based on experience of entomologists in Nebraska and other western states, while research is being conducted to better understand this cutworm’s response to Iowa conditions. IPM has taken a central role in modern commercial crop production that entails constant readjustment in crop management plans as observations, understanding of crop and pest development, technology and economics change. IPM in the 2000s For more than 40 years, average Iowa farm sizes have steadily increased concurrently with a decrease in the number of farms operations, while total acreage farmed in Iowa is essentially unchanged (Figures 1 and 2). 116 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 117 The trend of fewer operators on larger farms has implications to crop management systems. But perhaps an equally important change from the increase in average farm size is the shift toward both extremes in farm size. So the average farm size is still that, but many operations now fall farther and farther to the extreme in farm size. Figure 1. Average Iowa farm size 1975--2007. Table 2. Iowa farm size trends from 1974 to 2002. Under 50 acres 14,652 (11.6%) 21,089 (23.3%) 50—499 acres 97,098 (77.0%) 48,969 (54%) 500 acres or greater 14,374 (11.4%) 20,597 (23.1%) 2000 acres or greater 150 (0.1%) 1,321 (1.4%) 126,124 90,655 Total number of farms ft 2002 Many of the smallest farms are either diversified, producing specialty organic or niche crops, or are dedicated to production of high unit-value crops like wine grapes or other fruits or vegetables. The larger farm units are nearly all dedicated to corn and soybean production. In addition, the percentage of farm operators who engage in part-time off-farm employment increased from 26% in 1950 to 55.7% in 2002. This stratification of farm size and increase in off-farm employment has done several things. One is that for corn and soybean production there are increasingly fewer producers making decisions about more and more acres, perhaps with increasingly reduced time. As farms have consolidated, often agricultural service providers have consolidated in turn. The reduction in numbers of agricultural service providers means that the information flow from applied research to the growers who use the information must be channeled appropriately. ra d Figure 2. Number of farm operators 1975--2007. 1974 Conclusions Although it may seem on the surface that some pest problems have been simplified or solved by technological advancements, the need for integrated pest management in Iowa crop production will remain. As both input costs and commodity value fluctuate and as established pests adjust to technologies and new pest problems arise, challenges will remain. Economic thresholds that drive pest management decisions may change, but IPM will remain as a key to economic and environmental sustainability. The biggest challenges will be maintaining communication between applied researchers, private and public sector agronomists and farmers. Assessment of pest populations and crop conditions must be designed that are easy for growers to understand and implement, while the results gained are still valid. d ra ft Farm size group: Kogan, M.& Prokopy, R. (2003). Agricultural entomology. In Encylopedia of Insects, eds. V. H. Resh & R. T. Card´e, pp. 4–9. San Diego, CA: © academic Press. National Agricultural Statistics Service. Census of Agriculture, 1974. Washington, DC: United States Department of Agriculture. d ra ft National Agricultural Statistics Service. Census of Agriculture, 2002. Washington, DC: United States Department of Agriculture. Soybean aphid and potato leafhopper thresholds: Revisiting IPM decision support for soybeans and alfalfa in a high value field crop commodity rotation Eileen M. Cullen, Assistant Professor, Entomology, University of WisconsinMadison After attending this workshop, participants will gain knowledge necessary to: • Define the IPM terms economic injury level, economic threshold, damage boundary, and gain threshold. • Answer the question, “do insect economic thresholds change with higher crop prices?” ft Gray, M. E., Ratcliffe, S. T. and Rice, M. E. (2009, in press). Chapter 1: The IPM Paradigm: Concepts, Strategies and Practices. In Integrated Pest Management, eds. Edward B. Radcliffe, William D. Hutchison and Rafael E. Cancelado, pp. 1—13 Published by Cambridge University Press. © Cambridge University Press. 2008 Integrated Crop Management Conference - Iowa State University — 119 • Identify the components that make up an insect economic injury level • Understand why the soybean aphid economic threshold of 250 aphids/plant does not change when soybean prices increase from $5.50/bushel to $15.00/bushel. • Understand how potato leafhopper economic thresholds in alfalfa may help preserve long-standing biological control success for alfalfa weevil. ra References Background The National Research Council (1989) equated integrated pest management (IPM) adoption in field and forage crops with pest scouting and use of economic thresholds before a decision is made to apply insecticide. Three IPM terms and definitions are important for discussion purposes and data review during this workshop presentation. Economic Injury Level (EIL): The EIL is defined as the lowest number of insects that will cause economic damage (i.e., amount of pest injury justifies cost of insecticide application given control costs and value of the crop (Pedigo 1989). Economic Threshold (ET): The ET is set below the EIL to allow lead time to arrange insecticide treatment and suppress an insect population before it reaches the EIL (Stern et al. 1959). The ET is based on an understanding of population dynamics and growth rates for the particular insect pest. By setting the ET at a lower value than the EIL, we are predicting that once the population reaches the ET, chances are good that it will grow to exceed the EIL. Economic thresholds are also referred to as “action thresholds” or simply “thresholds”. That is, the point at which treatment is recommended to prevent pest populations from reaching the EIL. d 118 — 2008 Integrated Crop Management Conference - Iowa State University Damage Boundary: The number of a pest insect that must be present before its injury can be measured as yield loss (Pedigo 1989). Regardless of crop price, there is no reason to spend money, effort, or environmental impact to control insects that are present in numbers fewer than the damage boundary because there will not be any observable return in protected yield and there can be detrimental effects on natural enemy insects (Tollefson et al. 2008). 120 — 2008 Integrated Crop Management Conference - Iowa State University Keeping in mind that the economic threshold (i.e., the insect population density at which control action is taken) is already set below the economic injury level, the question we really need to be asking is do insect Economic Injury Levels (EILs) change with higher crop prices? Yes, the calculation of an EIL for an insect is a continuing process because new values are required with changes in the input variables. Consequently, when crop market value, management costs, and/or plant susceptibility change, recalculation of the EIL is necessary (Pedigo 1989). How do entomologists determine the economic injury level (EIL)? The full EIL equation incorporates cost of treatment per acre (C), value of the crop (V), yield potential of the crop (Yp), statistical coefficients from the linear regression relationship between insects per plant and yield loss (a and b), and the proportion of control that can be achieved by treatment (K). However, the basic formula for calculating the EIL can be condensed as written below (Pedigo 1989). The take-home message is that the EIL includes more than just the cost of treatment per acre and market value of the crop. EIL = gain threshold loss per insect Management costs ($/acre) = bushels/acre Market value ($/bushel) For example, if management costs for application of an insecticide are $18 per acre and harvested corn is marketed for $5.00 per bushel, the gain threshold would be 3.6 bushels per acre. The gain threshold is an important measure because it represents a basic margin for determining benefits of management and establishing treatment decision parameters (Pedigo 1989). The gain threshold is a basic break-even analysis and can be calculated as a first step when determining the EIL (Pedigo et al. 1986). d However, in order to determine the Economic Injury Level, we need more than the gain threshold, we also need to know how much yield loss the insect pest population causes at various population densities. Farmers and consultants need reliable information on the statistical relationship between insect pest population levels and crop yield loss, an estimate of yield loss per insect. To estimate the damage per insect, research plots are set up with various-sized insect populations on a crop at specific growth stages. Depending on the crop and insect pest combination, and on how the study is designed, various-sized insect population treatments may be established by infesting plots or caged plants with specific numbers of the pest insect, or by manipulating insect population levels using different rates and timing of insecticide application. Subsequently, yields are measured at the end of the season for grain crops, or at cutting for alfalfa harvest, and statistical procedures are used to determine the loss per insect. Entomologists use linear regression analysis, a statistical procedure, to analyze field research data and determine the relationship between number of insects per plant and yield loss. We need this information over a wide range of insect pest densities, even very low levels of insect pest populations. It’s actually very useful for farmers and IPM consultants to know with a high For insect pest/crop combinations when the relationship between insects per plant and yield loss cannot be approximated by a straight line (i.e., it is curvilinear), a more complex form of the EIL equation must be used. ra level of certainty that insect pest densities below a certain level will not cause measurable yield loss in experiments. In other words, at a certain point insect numbers are low enough that there is no yield difference between treated and untreated plots. Regardless of how high crop prices go, there is no benefit or need to treat below the damage boundary. Conversely, as long as the insect population is above the damage boundary, increasing crop prices may lead to a decrease in the EIL. Under these conditions, a lower insect pest population causes injury that justifies insecticide application given the higher value of the crop. Revisiting IPM decision support for field and forage crop insect pests North Central region field and forage crops are intimately linked as alfalfa is the primary perennial legume crop in rotation with annual commodity crops. This agricultural system is undergoing rapid change in terms of increasing crop prices, and the proportion of acreage planted to each of these crops. In Wisconsin, for example, a significant shift occurred in 2007 when farmers planted 4.1 million acres of corn – 11% more than in 2006. Many of these corn acres came from soybean acres. In 2008, soybeans returned to average state level (1.7 million acres), while winter wheat increased to 350,000 acres (a 40% increase from 2006). By contrast, Wisconsin alfalfa remained constant at 2.4 million acres from 2003 to 2008 and new seedings decreased by 26% from 500,000 acres in 2007 to 370,000 acres in 2008 (data: USDA NASS 2008). Corn and soybean crop prices have increased significantly and remained favorable over the last two to three years, due in part to surging investment in biofuels. In 2007, alfalfa prices increased sharply, partly due to tight hay supplies and partly in response to rapid increase in corn costs exerting upward pressure on forage value (Mintert 2008). d = ra Gain threshold ft In order for entomologists to calculate the EIL, we need to know the straightforward values such as cost of treatment per acre, and value of crop per acre (grain crops) or per ton (alfalfa hay). Looking strictly at the economics of an insect pest management decision, entomologists and IPM practitioners first consider the gain threshold. The gain threshold is expressed in amount of harvestable yield; when cost of suppressing insect injury equals money to be gained from avoiding the damage. The gain threshold is expressed as: 2008 Integrated Crop Management Conference - Iowa State University — 121 ft Do insect economic thresholds change with higher crop prices? Farmers and consultants are questioning whether to lower economic thresholds (ET) and apply insecticide at lower insect pest densities in field and forage crop systems. The EIL and ET levels for soybean aphid, Aphis glycines Matsumura, were developed quite recently and published in 2007 (Ragsdale et al. 2007). By comparison, EIL and ET levels for potato leafhopper, Empoasca fabae (Harris), in alfalfa were first developed over 20 years ago (Cuperus et al. 1983). Although potato leafhopper (PLH) economic thresholds have been revisited for PLH-resistant glandular haired alfalfa varieties (Lefko et al. 2000), hay and forage producers ask frequently if they should Case study 1: Soybean aphid economic threshold ft A common question during the 2008 growing season was … “The price of beans needs to be factored into the threshold in some way. Do $15 soybeans mean we lower the economic threshold below 250 aphids/plant?”. The economic threshold of 250 aphids/plant has not changed. ra The soybean aphid economic threshold is valid through the R5 stage. Replicated field plot research was conducted over 3 years, in 19 yield-loss experiments, across 6 states (Iowa, Michigan, Minnesota, Nebraska, North Dakota, and Wisconsin). This data set was used to determine the relationship between number of aphids/plant and yield loss across a range of aphid densities and soybean varieties. The economic threshold (ET) of 250 aphids/plant is set below the economic injury level (EIL). When the research was conducted 2004, 2005, 2006, soybean prices were $5.50-$6.50/ bushel. At that time the EIL, or number of aphids that need to be present for the value of the lost yield to equal the costs of control, was approximately 674 aphids/plant. d Now that market value for soybeans has increased, a lower EIL can be calculated (based on the linear regression analysis of the relationship between soybean aphid/plant and soybean yield over a wide range of densities, over three years across 6 states). David Ragsdale, the lead author of the Economic Threshold study (Journal of Economic Entomology 100: 1258-1267) re-calculated the EIL. For example, for soybeans selling at $15/bushel, with $8/acre control costs, and anticipated yield of 50 bu/acre. The EIL is lowered from 674 aphids/plant to 450 aphids/plant. The economic threshold (i.e., insect population density at which control action is taken) of 250 aphids/plant is still below this revised EIL of 450 aphids per plant. When soybean prices were $5.50-$6.50/bushel, the ET of 250 aphids/plant allowed 7 days lead time to treat before reaching the EIL of 674 aphid/plant. A lower EIL (450 aphids/plant) given higher soybean prices, simply reduces the lead time to 3-4 days to treat before reaching the EIL. Thus, the economic threshold of 250 aphids/plant has not changed. For an excellent, detailed explanation of the Upper Midwest research data behind the soybean aphid economic threshold of 250 aphids/plant and Economic Injury Level, please see the Plant Management Network web seminar with voice narration. It takes about 26 minutes to view the slide set. Access the presentation by Dr. Dave Ragsdale, University of Minnesota, at: http://www.plantmanagementnetwork.org/edcenter/seminars/SoybeanAphid/ From the link above, click on “Part II: Soybean Aphid: Economic Threshold and Economic Injury Level”. In our research across the Upper Midwest, using the common experimental protocol detailed in the web seminar above, treating below 250 aphids/plant resulted in NO detectable yield increase. 250 aphids/plant is not where injury begins, it is below the damage boundary. The economic threshold of 250 aphids/plant provides lead time to treat the field within a few days to prevent it from reaching the revised EIL of 450 aphids/plant. Case study 2: Potato leafhopper economic thresholds Initial research that established an economic injury level and economic thresholds for potato leafhopper on alfalfa was conducted between 1979-1981 in Minnesota (Cuperus et al. 1983). This research was performed on established alfalfa stands in 0.25 acre plots. Rather than infesting plots, or caging plants within plots, natural infestation potato leafhopper population densities were manipulated across treatments by cutting practices (maintaining uncut alfalfa refuges from which potato leafhoppers could infest treatment plots) and application of insecticides. Potato leafhoppers were sampled weekly during 2nd and 3rd crops, at various crop heights ranging from 2 to 21 inches. Similar to soybean aphid EIL studies (Ragsdale et al. 2007), potato leafhopper abundance was expressed as potato leafhopper/sweep/week. Cumulative numbers are used because damage potential depends on duration of infestation, population density, and alfalfa height when infestation occurs. ft This workshop will explore two case studies. First, we review the recent North Central region university research data (Ragsdale et al. 2007) for soybean aphid yield-loss measurements across six states over three years, and a wide range of soybean prices, including recent high prices in the ‘teens’. Second, we review existing yield-loss relationship data for potato leafhopper in alfalfa and the link between leafhopper insecticide application timing and parasitoids responsible for alfalfa weevil biological control. 2008 Integrated Crop Management Conference - Iowa State University — 123 In this original work (Cuperus et al. 1983), the potato leafhopper EIL was defined as the number of cumulative potato leafhopper/sweep/week that caused a yield loss reduction equivalent in value to the cost of control. The study used a control cost of $6.50 per acre application cost of dimethoate, and 1983 alfalfa crop values calculated based on cost of replacement feeds (soybean meal; corn) at the time. In summary, this original work established an economic injury level of approximately 0.74 potato leafhoppers (PLH) per sweep; and economic thresholds for a range of alfalfa heights: 0.32 PLH/sweep at 2 inches, 0.40 PLH/sweep at 5 inches, and 0.5 PLH/sweep at 7 inches. ra treat below established economic thresholds on PLH-susceptible (normal) alfalfa varieties, given increasing alfalfa hay prices (Holin 2008). Compared to the research data set for soybean aphid economic injury levels and economic threshold where the damage boundary is known (Ragsdale et al. 2007), potato leafhopper studies have not yet identified the damage boundary on alfalfa. Cuperas et al. (1983) did show that alfalfa dry-matter yield loss per potato leafhopper is a curvilinear relationship, with more yield loss at low leafhopper numbers than at high leafhopper numbers. However, their economic injury level and economic thresholds summarized above took this relationship into account. Moreover, the potato leafhopper economic thresholds in use today for non-glandular haired varieties (DeGooyer et al. 1998; Lefko et al. 2000) are more conservative than those originally calculated by Cuperas et al. (1983). d 122 — 2008 Integrated Crop Management Conference - Iowa State University Current potato leafhopper economic thresholds on alfalfa are 0.1 potato leafhopper (nymphs and/or adults) per 15 inch diameter sweep net sample for each 1 inch of plant height, if the alfalfa is < 10 inches tall, and > 2 potato leafhoppers per sweep if the alfalfa is taller than 10 inches (DeGooyer et al. 1998, Rice 1996, Boerboom et al. 2008). For example, the economic threshold for 6 inch alfalfa is reached at 5 potato leafhoppers/10 sweeps, or 0.5/sweep. Taller plants are able to tolerate more leafhoppers (Wilson et al. 1989). If the economic threshold is reached on tall alfalfa within 7 days of planned harvest, the cultural control of early harvest is advised, rather than insecticide treatment (Undersander et al. 2004). 124 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 125 Koshel, P. and K. Mcallister. 2008. Transitioning to sustainability through research and development on ecosystem services and biofuels: workshop summary. National Research Council, National Academies Press, Washington, DC. Potato leafhopper represents the pivotal insecticide use decision for Wisconsin farmers each year in alfalfa, a crop with several attributes, as described above, which make it an excellent candidate for the application of IPM approaches. Pedigo, L.P. 1989. Entomology and Pest Management, Macmillan Publishing Company, New York, NY. This workshop will conclude with a discussion of how current economic threshold treatment decision support for potato leafhopper in alfalfa will continue to provide IPM decision support allowing growers and advisors to benefit from highly effective potato leafhopper insecticide management tactics, while re-focusing on the importance of scouting-based economic threshold treatment decisions to preserve long-standing biological control success for alfalfa weevil. References d Boerboom, C., E. Cullen, P. Esker, R. Flashinski, C. Grau, B. Jensen, and M. Renz. 2008. Pest management in Wisconsin field crops. University of Wisconsin-Extension, Publication A3646. Cuperus, G.W., E.B. Radcliffe, D.K. Barnes, and G.C. Marten. 1983. Economic injury levels and economic thresholds for potato leafhopper (Homoptera: Cicadellidae) on alfalfa in Minnesota. Journal of Economic Entomology 76: 1341-1349. DeGooyer, T.A., L.P. Pedigo, and M.E. Rice. 1998. Evaluation of grower-oriented sampling techniques and proposal of a management program for potato leafhopper (Homoptera: Cicadellidae) in alfalfa. Journal of Economic Entomology 91: 143-149. Flanders, K.L. and E.B. Radcliffe. 2000. Alfalfa IPM. In Radcliffe’s IPM World Textbook, University of Minnesota. (http://ipmworld.umn.edu/chapters/flanders.htm). Holin, F. 2008. Should insect thresholds be lowered? Hay and Forage Grower Magazine, May 1, 2008. (http://hayandforage.com/hay/alfalfa/0501-insect-thresholds-lowered/). Mintert, J. 2008. Forage prices haven’t yet caught up with corn prices. Beef Magazine, July 11, 2008. (http://beefmagazine.com/cowcalfweekly/0711-forage-prices-caught-corn-prices/). ft National Research Council. 1989. Alternative agriculture. National Academy Press, Washington, DC. Pedigo, L.P., S.H. Hutchins, and L.G. Higley. 1986. Economic injury levels in theory and practice. Annual Review of Entomology 31: 341-368. Radcliffe, E.B. and K.L. Flanders. 1998. Biological control of alfalfa weevil in North America. Integrated Pest Management Reviews 3: 225-249. Rice, M.E. 1996. Leafhoppers on the increase. Integrated Crop Management. Iowa State University Extension IC-476 (17): 116-117. Ragsdale, D. W., B. P. McCornack, R. C. Venette, B. D. Potter, I. V. MacRae, E. W. Hodgson, M. E. O’Neal, K. D. Johnson, R. J. O’Neil, C. D. Difonzo, T. E. Hunt, P. A. Glogoza, and E. M. Cullen. 2007. Economic threshold for soybean aphid (Hemiptera: Aphididae). Journal of Economic Entomology 100: 1258-1267. ra ra Current potato leafhopper economic thresholds appear conservative enough to protect against dry-matter yield loss in the current high value hay market. At this time, university research does not support lowering potato leafhopper economic thresholds below the current 0.1 PLH/sweep for each 1 inch of plant height. Additional field research quantifying “no effect” (i.e., damage boundary) when alfalfa is treated below current economic thresholds would be useful and preliminary studies in Wisconsin aim to obtain these data. Lefko, S.A., L.P. Pedigo, and M.E. Rice. 2000. Alfalfa stand tolerance to potato leafhopper and its effect on the economic injury level. Agronomy Journal 92: 726-732. Schmidt, N.S., M.E. O’Neal, and J.W. Singer. 2007. Alfalfa living mulch advances biological control of soybean aphid. Environmental Entomology. 36: 416-424. Stern, V.M., R.F. van den Bosch, and K.S. Hagen. 1959. The integrated control concept. Hilgardia 29: 81-101. Tollefson, J., M. O’Neal, and M. Rice. 2008. Reviewing Decision Thresholds for Pest Insect Control. Integrated Crop Management News, July 30, 2008. (http://www.extension. iastate.edu/CropNews/2008/0730tollefsonriceoneal.htm). d ft Finally, alfalfa supports a diverse population of insect species. In addition to potato leafhopper, key insect pests in Wisconsin and the North Central region include alfalfa weevil, Hypera postica (Gyllenhal), and a complex of aphid species dominated by pea aphid, Acyrthosiphon pisum (Harris). The rest are local, sporadic or incidental herbivores, and many are beneficial insect predators and parasitoids, or pollinators (Flanders and Radcliffe 2000). A highly successful importation biological control project for alfalfa weevil in the Midwest established multiple parasitoid species that have nearly eliminated the need for insecticide application against alfalfa weevil (Radcliffe and Flanders 1998). Moreover, alfalfa provides an ecosystem service (Koshel and Mcallister 2008) as habitat for beneficial insects important to annual crop/pest combinations such as soybean/soybean aphid (Schmidt et al. 2007). Undersander, D., Becker, R., Cosgrove, D., Cullen, E., Doll, J., Grau, C., Kelling, K., Rice, M.E., Schmitt, M., Sheaffer, C., Shewmaker, G., Sulc, M. 2004. Alfalfa Management Guide. NCR547 North Central Regional Extension Publication. USDA NASS (U.S. Department of Agriculture National Agricultural Statistics Service). 2008. USDA National Agricultural Statistics Service – Quick Stats, Wisconsin Data – Crops. USDA, Washington, DC. (http://www.nass.usda.gov/QuickStats/Create_Federal_Indv.jsp). Wilson, M.C., M. C. Shaw, and M.A. Zajac. 1989. Interaction of the potato leafhopper and environmental stress factors associated with economic and damage thresholds for alfalfa. In Proceedings of a symposium: history and perspectives of potato leafhopper (Homoptera: Cicadellidae) research. E.J. Armbrust and W.O. Lamp, Eds., Miscellaneous publications of the Entomological Society of America, no. 72. College Park, MD. 126 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 127 Focus on insects: A review of the top 5 research articles in agricultural entomology ft The scientific literature contains a wealth of new information on insect biology, ecology, behavior and management, but seldom does this research directly reach the crop advisor or agri-business professional. During the last 12 months, numerous research papers have been published that may have relevance to crop production and management in Iowa. Five of these scientific papers were selected from the scientific journals Environmental Entomology, Journal of Economic Entomology or Nature Biotechnology and the published abstracts are presented. Free PDFs of all but the Bt theory paper can be accessed at http://www.entsoc.org/Pubs/ Overview/index.htm. The objective of this presentation is to create awareness of this newly published research by briefly presenting an overview of the significant findings and the implications for agriculture in Iowa. ra Is preventative, concurrent management of the soybean aphid (Hemiptera: Aphididae) and bean leaf beetle (Coleoptera: Chrysomelidae) possible? K. D. Johnson, M. E. O’Neal, J. D. Bradshaw, and M. E. Rice. 2008. Journal of Economic Entomology 101: 801-809. Abstract In Iowa, the management of insect pests in soybean, Glycine max (L.) Merr., has been complicated by the arrival of the invasive species soybean aphid, Aphis glycines Matsumura (Hemiptera: Aphididae), and occasional outbreaks of bean leaf beetle, Cerotoma trifurcata (Förster) (Coleoptera: Chrysomelidae), populations leading to economic losses. Several insecticide programs designed to reduce abundance of the overwintered and first generation C. trifurcata and the incidence of bean pod mottle virus were evaluated over 3 yr (2004-2006) for their impacts on A. glycines populations, at three locations in Iowa (Floyd, Lucas, and Story counties). There was no significant overlap of either overwintered (early May) or the first (early July) generations of C. trifurcata with A. glycines, because aphids were first detected in June and they did not reach economically damaging levels until August, if at all. During this study, insecticides targeting the overwintered population or the first generation of C. trifurcata provided a limited impact on A. glycines populations compared with untreated controls, and they did not prevent economic populations from occurring. Furthermore, the highest populations of A. glycines were frequently observed when a low rate of lambda-cyhalothrin (178 ml/ha) was applied targeting the overwintered population of C. trifurcata. Soybean yields were not protected by any of the insecticide treatments. Our results indicate that the use of either early season foliar or seed-applied insecticides for C. trifurcata management is of limited value for A. glycines management. d d ra ft Marlin E. Rice, Professor, Entomology, Iowa State University 128 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 129 Bottom line Insect resistance to Bt crops: Evidence versus theory. Insecticides applied against overwintered and first generation (early July) bean leaf beetles had little effect on soybean exposure to soybean aphid. No treatment during the three-year study had any effect on yield. Management of overwintered and first generation bean leaf beetles, and soybean aphids is not currently possible with a single or multiple early season insecticide treatments. B. E. Tabashnik, A. J. Gassmann, D. W. Crowder, and Y. Carriére. 2008. Nature Biotechnology 26: 199-202. d Bottom line Management of both bean leaf beetle and Bean pod mottle virus with either a seed treatment, first generation targeted insecticide, or a combination of both is challenging and often produces inconsistent results. Seed treatments can be effective in reducing overwintered beetle populations during “low population” years but are ineffective during outbreak years. A seed treatment plus an insecticide applied against the first generation beetles (mid summer population) produced yields statistically greater (2.1-2.5 bu/acre) than the untreated check in only 3 out of 8 location-years. Bottom line ft ra Cerotoma trifurcata Förster (Coleoptera: Chrysomelidae) and Bean pod mottle virus (Comoviridae) (BPMV) both can reduce yield and seed quality of soybean, Glycine max (L.) Merr. Field experiments were conducted to evaluate the effects of systemic, seed-applied, and foliar-applied insecticides for the management of this pest complex at three locations in central, northeastern, and northwestern Iowa during 2002-2004. Seed-applied insecticide was evaluated according to a currently recommended management program for Iowa (i.e., insecticide applications that target emerging overwintered beetles, F0, and the first seasonal generation, F1). The experimental treatments included seed-applied (thiamethoxam, 0.3-0.5 g [AI] kg−1] or clothianidin, 47.32 ml [AI] kg−1) and foliar-applied (λ-cyhalothrin, 16.83-28.05 g [AI] ha−1) or esfenvalerate (43.74-54.69 g [AI] ha−1) insecticides. Applications of the foliar insecticides were timed to target F0, F1 or both F0 and F1 populations of C. trifurcata. Our results confirm that insecticides timed at F0 and F1 populations of C. trifurcata can reduce vector populations throughout the growing season, provide limited reduction in virus incidence, and improve both yield and seed coat color. Furthermore, seed-applied insecticides may be the more reliable option for an F0-targeted insecticide if used within this management strategy. An F0-targeted insecticide by itself only gave a yield improvement in one out of eight location-years. However, by adding an F1-targeted insecticide, there was a yield gain of 1.42-1.67 quintal ha−1, based on contrast comparisons at three location-years. Cotton bollworm (=corn earworm) has developed resistance to Cry1ac in cotton, but widespread crop failure has not been observed. European corn borer resistance to Cry1Ab has not been detected in 933 field populations. A model simulating percent refuge abundance on European corn borer resistance to Bt corn suggests a 5 percent refuge will delay the development of resistance by more than 20 years. ra Abstract ft J. D. Bradshaw, M. E. Rice, and J. H. Hill. 2008. Journal of Economic Entomology 101: 1211-1227. Evolution of insect resistance threatens the continued success of transgenic crops producing Bacillus thuringiensis (Bt) toxins that kill pests. The approach used most widely to delay insect resistance to Bt crops is the refuge strategy, which requires refuges of host plants without Bt toxins near Bt crops to promote survival of susceptible pests. However, large-scale tests of the refuge strategy have been problematic. Analysis of more than a decade of global monitoring data reveals that the frequency of resistance alleles has increased substantially in some field populations of Helicoverpa zea, but not in five other major pests in Australia, China, Spain and the United States. The resistance of H. zea to Bt toxin Cry1ac in transgenic cotton has not caused widespread crop failures, in part because other tactics augment control of this pest. The field outcomes documented with monitoring data are consistent with the theory underlying the refuge strategy, suggesting that refuges have helped to delay resistance. Frequency and severity of western bean cutworm (Lepidoptera: Noctuidae) ear damage in transgenic corn hybrids expressing different Bacillus thuringiensis Cry toxins. H. Eichenseer, R. Strohbehn, and C. Burks. 2008. Journal of Economic Entomology 101: 555-563 Abstract d Evaluation of management strategies for bean leaf beetles (Coleoptera: Chrysomelidae) and bean pod mottle virus (Comoviridae) in soybean. Abstract The frequency and severity of corn ear damage caused by western bean cutworm, Striacosta albicosta (Smith), were measured on transgenic corn, Zea mays L., hybrids expressing two different insecticidal Bacillus thuringiensis (Bt) (Berliner) Cry toxins (Bt) selected to protect against damage caused by larval European corn borer, Ostrinia nubilalis (Hübner). A field cage experiment deliberately infested with western bean cutworm egg masses resulted in less damage in the hybrid expressing the Cry1F protein and supported fewer western bean cutworm larvae than its non-Bt isoline. Corn hybrids expressing Cry1F, grown in small plot field experiments at three locations over two separate years and exposed to natural western bean cutworm infestations suffered less damage than non-Bt or Bt-hybrids expressing a Cry1Ab protein. Later maturing hybrids suffered more damage than shorter-season hybrids. Finally, corn ears observed in strip trials for several years in diverse agronomic conditions in farmer-cooperator fields corroborated the in-plant protection conferred by corn hybrids expressing the Cry1F protein in small plot field trials. Prairie grasses as hosts of the northern corn rootworm (Coleoptera: Chrysomelidae). Abstract ft I. Oyediran, B. W. French, T. L. Clark, K. E. Dashiell, and B. E. Hibbard. 2008. Environmental Entomology 37: 247-254. d ra We evaluated 27 prairie grass species thought to be among those dominant 200 yr ago in the northern midwest as larval hosts of the northern corn rootworm, Diabrotica barberi Smith and Lawrence. Maize (Zea mays L.), spring wheat (Triticum aestivum L.), and grain sorghum (Sorghum bicolor L.) were included as controls for a total of 30 species. Twenty pots of each species were planted in a randomized complete block design. Each pot was infested 5 wk later with 20 neonate northern corn rootworm larvae. Two pots within each species and block were assigned an extraction date of 7 or 14 d after infestation. The remaining two pots from each block were used to monitor adult emergence. The percentage of larvae recovered, change in larval head capsule width, and change in average dry weights varied significantly among the grass species. The highest percentage of larvae was recovered from slender wheatgrass, Elymus trachycaulus (Link), and this was significantly greater than the percentage recovered from all other species including maize for the 14-d sample date. Several additional species were also relatively good hosts, in that the percentage of larvae recovered from these species was not significantly different from maize. The average dry weight of larvae recovered was significantly greater for larvae recovered from maize than for larvae recovered from all other species except slender wheatgrass, when the two samples dates were combined. Overall, adults were produced from only 6 of the 28 species evaluated, and no analysis was performed because of the low numbers. The results of this study are discussed in relation to the potential of alternate hosts of northern corn rootworm to serve as a bridge to survival on transgenic maize. Bottom line The best host for northern corn rootworm larvae was slender wheatgrass (number of larvae recovered 14 days after infestation). Fewer larvae, but statistically equal numbers, developed on corn, Canada wildrye, big bluestem, Indian grass, and prairie cord grass. Little bluestem produced even fewer larvae and no larvae survived on sorghum. Aphid resistant soybeans: Will they prevent soybean aphid outbreaks? Matthew E. O’Neal, Assistant Professor, Entomology, Iowa State University Mariana Chiozza, Graduate Research Assistant, Entomology, Iowa State University Since the invasion of the soybean aphid to the US, efforts to locate aphid resistance in soybean germplasm has resulted in several success. At least 3 different sources of resistance have been located, constituting mostly antixenosis and antibiosis. Host plant resistance against the soybean aphid has been incorporated into commercially available varieties that can be grown within the North Central region of the US. In 2009, these commercially sources will include the RAG1 gene. Soybean-checkoff funded research has revealed that this gene will reduce aphid populations and reduce yield loss during aphid outbreaks, compared to a related susceptible variety. However, RAG1-containing soybeans will not be aphid free, nor will yields be optimized without an insecticide application. In this brief summary, we discuss the performance of RAG1soybean in Iowa during 2007 and 2008. During the presentation at the ICM conference, we discuss the utility of aphid-resistance soybeans in light of increasing commodity and input costs. ft Herculex hybrids (event TC1507, Cry1F) had significantly fewer ears with western bean cutworm damage, significantly lower ear damage scores, and occasionally fewer moldy kernels than YieldGard hybrids (event MON810, Cry1Ab) and non-Bt hybrids. across all hybrids, damage was greater in late maturing hybrids than early and mid-season maturing hybrids. 2008 Integrated Crop Management Conference - Iowa State University — 131 In 2007 we examined soybeans containing the RAG1 gene in replicated field plots in Story Co. Iowa. We compared a soybean variety containing RAG1 to a parental line that did not have this resistance-henceforth referred to as susceptible. The RAG1 gene confers a degree of antibiosis against soybean aphids (Hill et al. 2004). Antibiosis is a form of resistance in which the insect fails to reproduce, and in certain situations dies on the plant. As we have seen during our two years of study, soybean aphids in Iowa can survive on RAG1-containing soybeans. Therefore we wanted to determine if RAG1 provided some level of tolerance to aphids. Tolerance is an uncommon form of resistance in which the pest can survive and build large populations on the plant, but yield is not affected. To test for tolerance we split each plot in half, leaving one half unprotected from aphids and repeatedly spraying the other with an insecticide (lambdacyhalothrin). We observed a significant difference in the number of aphids on resistant versus susceptible soybeans. By comparing the aphid-free to the untreated plots we can account for the yield impact of aphids on resistant and susceptible plants. ra Bottom line d 130 — 2008 Integrated Crop Management Conference - Iowa State University Populations peaked at 3,404 aphids per plant on 31 July, 2007 on susceptible plants while the resistant plants reached 497 aphids per plant. Throughout the season susceptible plants experienced 5 times the exposure of resistant plants. Although a significant reduction, previous research on soybean aphids (Ragsdale et al. 2007) indicates yield loss can occur when 10,000 aphid days are accumulated. Aphids had significantly reduced yield in the susceptible but not the resistant soybeans (Fig. 1). Our experiment does not indicate the presence of tolerance. Note that the difference between the aphid free and infested plots for the resistant line was 8 bushels and the same comparison for the susceptible line was 32 bushels; a 4-fold level of yield protection due to host plant resistance. This is very close to the difference in aphid exposure between the resistant (11,396 average CAD) and susceptible lines (59,513 average CAD); approximately a 5-fold difference. So the benefit of RAG1 appears to be antibiosis alone. That soybean aphids can survive on RAG1-contianing soybeans is not limited to Iowa (Kim et al. 2008). The discovery of biotypes that can survive on RAG1-soybeans with no detrimental 132 — 2008 Integrated Crop Management Conference - Iowa State University Hill, C.B., Y. Li, and G. L. Hartman. 2004. Resistance to the soybean aphid in soybean germplasm. Crop Sci. 44: 98-106. d Kim, K.-S., C. B. Hill, G. L. Hartman, M. A. R. Mian, and B. W. Diers. 2008. Discovery of soybean aphid biotypes. Crop Science. 48: 923-928. A 75 AB Average bushels per 65 acre (+SEM) B 55 C ft 45 35 soybean aphid resistant soybean aphid susceptible Figure 1. Comparison of resistant and susceptible soybeans kept free from aphids using a foliage-applied insecticide or left untreated. Different letters indicate statistically significant different in yield (P=0.05). Source of the resistant is the RAG1 gene. ra References. No insecticide applied 8000 7000 aphid resistant (RAG1) 6000 aphid susceptible 5000 4000 d ra Host plant resistance as a insect pest management tool has produce remarkable reductions in pest pressure, especially regarding genetically modified corn that is resistant to European cornborer or corn rootworms. However, as demonstrated above, conventionally developed host plant resistance for soybeans aphids has yet to produce a variety that is free of aphids, to the same degree as Bt-corn. As soybean aphid resistance becomes commercially available, it will likely require additional pest management tools for the optimal yield to be produced. For growers who scout and employ the 250 aphid per plant threshold, the RAG1-soybeans can be a useful supplement but not a replacement management tactic. Growers who want their fields aphid-free will be disappointed. However, the good news is that growers do not need aphid-free soybeans to reach optimal yields, as will be discussed by Kevin Johnson and Dr. Eileen Cullen later today during sessions C, D, E, and F. Aphid free-insecticide applied 3 times Average aphids per plant (+SEM) ft effect to their longevity or reproduction has been reported for aphids collected in Ohio. When we repeated this experiment we saw even larger populations on RAG1-soybeans in 2008 (Fig. 2) as in 2007. This is likely due to a larger numbers of aphids immigrating into Iowa and not the spread of the biotype. If it had been the biotype, as described by Kim et al. (2008) I would not have expected the population size to be different between the resistant and susceptible lines. Although, RAG1 does not keep the plant aphid-free, in both 2007 and 2008 we have observed significantly fewer aphids on the resistant lines. Aphid populations will develop and build slowly on resistant plants, reaching the economic threshold after such populations were reached on an adjacent susceptible plants. Since current recommendation is based on applying an insecticide within 7 days of aphid populations exceeding the economic threshold, this slowing of aphid population growth may be a significant buffer for growers trying to manage an aphid outbreak. 2008 Integrated Crop Management Conference - Iowa State University — 133 3000 2000 1000 0 11Jul 18Jul 25Jul 1Aug 8Aug 15Aug 22Aug 29Aug 5Sep 12Sep Figure 2. Soybean aphid populations on a susceptible (empty boxes) and resistant soybean line (grey diamonds) that contains the RAG1 gene. Aphid populations were calculated based on an averge (+SEM) for 10 plants from 4 replicated plots in Story County IA during the 2008 growing season. 134 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 135 What have we learned over five years of soybean aphid management using insecticides? Kevin D. Johnson, Graduate Research Assistant, Entomology, Iowa State University Matthew E. O’Neal, Assistant Professor, Entomology, Iowa State University ft Soybean, Glycine max (L.), grown in Iowa and most of the north-central region of the United States has historically used low amounts of insecticide. However, an invasive insect pest has threatened soybean production in Iowa, with the arrival of the soybean aphid (Aphis glycines Matsumura). The soybean aphid causes yield losses from direct plant feeding, and has been shown to transmit several plant viruses. In Iowa, soybean aphid colonize soybean fields beginning in June and has produced outbreaks in July and August capable of reducing yields by nearly 25% (Johnson 2006). ra Research conducted at Iowa reseach farms over the last five years has added to our knowledge and understanding of this new pest. We know that the presence of the aphid is not enough to warrant the application of an insecticide; populations above 600 aphids per plant are typically needed to produce measurable yield lose. Based on several years’ worth of replicated field trials, we have developed a recommendation that incorporates an economic threshold of 250 aphids/ plant (Ragsdale et al. 2007). We also know that natural enemies, like ladybeetles, can have a significant impact on aphid populations (Schmidt et al. 2007). However many questions remain when it comes to soybean aphid management: • What products offer the most consistent control of soybean aphids? • How does the 250 aphids per plant threshold compare to lower thresholds over the last five years? • Should aphids be treated when the exceed the economic threshold on late stage soybeans (i.e. R6-stage)? d d ra ft Introduction We will answer all of these questions in the presentation. However for this article we will focus on answering the most common question we get from growers; what insecticides offer the most consistent level of control of soybean aphids under Iowa growing conditions? Materials and methods To answer this question we have evaluated the ability of various insecticides to manage soybean aphids for the past five years at the Iowa State University Northeast research farm in Floyd County. During 2008 we had a late soybean aphid outbreak in which we were evaluated 33 insecticides alone or in combination. Several of these insecticides are experimental and not yet approved for use in on soybeans in the US. In this summary, we will only present data for insecticides that are labeled for aphid control in Iowa soybeans (Table 1). We compare the ability of these insecticdse to reduce aphid populations and protect yield by comparing to soybeans either left untreated or kept aphid free. These additional treatments control for the impact of aphids on soybean growth. Our first control consisted of soybean grown with out any 136 — 2008 Integrated Crop Management Conference - Iowa State University Table 1. Insecticides and rates of the 2008 soybean aphid efficacy trials ∞  xi −1 + xi   × t 2  ∑ = ï£¬ï£ n =1 Timing of application2 --------- ----------- ----------- 1.9 oz λ-cyhalothrin 4 oz chlorpyrifos 10 1.9 oz λ-cyhalothrin 250 Cruiser 50 g thiamethoxam Seed applied Gaucho 62.5 g imidacloprid Seed applied Baythroid XL 2.8 oz 1 Aug Warrior II 1.9 oz b-cyfluthrin λ-cyhalothrin z-cypermethrin z-cypermethrin + bifenthrin 1 Aug chlorpyrifos 1 Aug clorpyrifos 1 Aug dimethoate 1 Aug 1 Aug 2 oz + 8 oz g-cyhalothrin + chlorpyrifos b-cyfluthrin + chlopyrifos 13 oz thiamethoxam 1 Aug Leverage 3.8 oz b-cyfluthrin + imidacloprid 1 Aug Endigo 2.8 oz λ-cyhalothrin + thiamethoxam 1 Aug Aphid free control 3 250 aphids pre plant 4 Mustang Max 4 oz Hero 8 oz Lorsban 4E 16 oz NuFos 16 oz Dimethoate 16oz Cobalt 13 oz Baythroid XL + Lorsban 4E Centric 1 Aug 1 Aug 1 Aug Rate is formulated product per acre for foliar products, and as grams active ingredient per 100 kilograms of seed. 1 Seed applied insecticides (SA) were applied to seeds prior to planting and foliar insecticides were applied when the average aphid per plant reached pre-determine levels represented by the number in this column. 2 The aphid free control was treated with insecticides four times (22 July, 1 August, and 22 August). All other foliar treatments were applied once (1 August). 3 d d Seasonal exposure of soybean to aphids is reported based on the accumulation of ‘aphid days’. Aphid days were calculated based on the number of aphids per plant counted between two sampling dates and is calculated with the following equation: active ingredient Untreated control ft ra Soybean aphids (winged adults, wingless adults, and immatures) were counted weekly (last week of May through the second week of September) on consecutive plants within each plot. The number of consecutive plants ranged from 5 to 20, with the number of plants counted determined by the proportion infested with aphids during the previous sampling date. When 0% to 80% of plants were infested with soybean aphid, soybean aphid on 20 plants were counted; when 81% to 99% of plants were infested, soybean aphid on 10 plants were counted; at 100% infestation, soybean aphid on 5 plants were counted. Plants were randomly selected from the center 4 rows within each plot. Rate1 ft Product trade name We evaluated the performance of each insecticide within a randomized complete block design experiment with each product replicated 6 times (Table 1). Plots measured 50’ in length and 15’ in width. Soybeans (NK 21-N6) were planted on 19 May using no-till production practices. Aphid populations averaged 6 aphids per plant 3 days prior to the application of the foliar insecticides on 1 August. Following the application of the foliar insecticides soybean aphid populations were assessed every 2-7 days for 21 days following insecticide application. At harvest, yields were recorded and corrected to 13% moisture. Estimation of aphid exposure 2008 Integrated Crop Management Conference - Iowa State University — 137 ra insecticide; we referr this as an untreated control. The second set of control plots was treated multiple times to prevent an aphid population from establishing; this is referred to as the ‘aphid free’ control. This was accomplished with a foliar insecticide that consisted of a combination of an organophosphate (Warrior II) and a pyrethroid (Lorsban 4E). We selected this combination as it can prevent spider mite outbreaks that can occur when pyrethroids are used alone. By comparing the untreated control to the aphid free control we can estimate the yield loss that occurred due to the soybean aphid. Furthermore, since the aphid-free treatment is applied when aphid populations were approximately 10 per plant, when aphid populations reach the economic threshold we can test this lower threshold to that of the 250 aphids per plant threshold to protect soybean yield. Applied 22 August. 4 equation [1] where x is the mean number of aphids on sample day i, xi-1 is the mean number of aphids on the previous sample day, and t is the number of days between samples i - 1 and i. Summing aphid days accumulated during the growing season or cumulative aphid days provide a measure of the seasonal aphid exposure that a soybean plant experiences. Statistical analysis We used analysis of variance (ANOVA) test to determine if 1) the exposure of plants to aphids and 2) yield differed amongst the various treatments. The impact of insecticides applied on the total accumulation of aphid days was determined using log-transformed data to reduce heteroscadascity and meet the assumptions of ANOVA. Treatment impacts on yield were determined using untransformed data. Means separation for all studies was achieved using the Student-Newman-Keuls least significant difference test. All statistical analysis was performed with SAS® software. ft We observed the lowest yields when soybeans were left untreated (Fig.1). The foliar applied insecticides we tested provided similar levels of soybean aphid control and yield protection (Fig. 1). Overall a single application of a foliar insecticide provided as much yield protection as four applications applied from 15 June to 13 August. The seed treatments we tested provided a lower level of soybean aphid control and lower yields as compared to all foliar applied insecticides (Fig. 1). d ra Although 2008 soybean aphid populations arrived late in the summer and did not reach economic populations until soybeans were in late reproductive growth stages, the trends observed are consistent with our past results. Again we observed little difference in performance amongst most of the foliar insecticides. The efficacy of the organophosphate (Dimethoate and Lorsban) and pyrethroid (Baythroid, and Warrior) insecticides was indistinguishable from each other. Combining pyrethroid and organophosphate insecticides did not improve aphid control or soybean yield compared to either class of insecticide applied alone. This was true even for a premixed product like Cobalt. However, when compared to the control treatment these tank-mixes provided a small increase in yield as compared to the untreated control. 2008 represents the first year foliar nicotinoids were available in Iowa, and these products performed well either alone (Centric) or in combination with a pyrethroid (Leverage and Endigo) providing yield protection. The most important issue for effective soybean aphid management is the timing of a foliarapplied insecticide (250 aphids per plant) and not the product selected. This is truly remarkable given the comparison to the aphid-free control, which would represent an economic threshold of 10 aphids per plant. The situation described in Figure 1 (First three treatments) was a common one for growers during the 2008 growing season. Aphid populations exceeded the ET (250 aphids per plant) in the R6 stage, which exceeds the growth stage range at which the ET is applicable (R1-R5). A limited data set (Ragsdale et al. 2007) suggests that soybeans can tolerate a greater aphid population than the EIL when the plant is in the later growth stages (R6 and on). Our data from 2008 suggest that yield loss did not occur when aphid exceeded the ET in the R6 stage. Note that the aphid population did not reach the EIL (654 aphids per plant). A better test would be one where late-season aphid populations exceeded the EIL. At this location that did not occur. However, this small study suggests that our ET should be increased as the soybean plant matures past the R5 stage. Compared to the foliar insecticides, the seed-applied insecticides did not provide as great a level of protection. Although we did observe some evidence of control between the untreated soybeans and the seed-treated soybeans, the variability among these treatments was great. Soybean aphid control from seed applied insecticides is not sufficient to protect plants from aphid outbreaks that occur in July or August, especially for soybeans planted in May. McCornack and Ragsdale (2006) showed that seed-applied insecticides are effective on soybean aphid, however this efficacy only lasts for the first month after planting (Johnson et al. 2008). Our recommendation for soybean aphid management continues to be to scout your fields and to apply foliar insecticides when populations exceed 250 aphids per plant on 80% or more of the crop (see Ragsdale et al. 2007 for a more detailed description). This recommendation is most appropriate for soybeans in the R1-R5 stage; as the plant passes the R5 stage growers should consider increasing the ET they use. However, we still do not know to what extant yield losses occur when aphids populations exceed the EIL (654 aphids per plant) on soybeans passed the R5 stage. We are not recommending seed-applied insecticides (seed treatments) for aphid management, and we are not recommending one insecticide over another. Over the five years we have been assessing insecticide efficacy Warrior, Baythroid, and Lorsban have performed equally well and the seed treatments have not prevented the need for a foliar insecticide in high aphid years. Multiple insecticide treatments have not protected yields compared to a single foliar insecticide application at 250 aphids per plant. References ft During the 2008 growing season aphid populations peaked on 22 August at 541 aphids per plant at this research farm. In general, all the insecticides applied reduced the exposure of plants to aphids compared to the untreated control, with the greatest reduction observed when a foliar insecticide was used. Note that the aphid free control did not reduce the exposure anymore than a single foliar application of any of the products tested. This lack of a significant difference occurred despite applying insecticides on three different occasions. 2008 Integrated Crop Management Conference - Iowa State University — 139 Johnson, K. D. 2006. Management of the soybean aphid, Aphis glycines Matsumura (Hemiptera: Aphididae), in Iowa. M. S. Thesis, Iowa State University, Ames, Iowa. Johnson, K.D, M.E. O’Neal, J.D. Bradshaw and M.E. Rice. 2008. Is Preventative, ConcurrentManagement of the Soybean Aphid (Hemiptera: Aphididae) and Bean Leaf Beetle (Coleoptera: Chrysomelidae) possible? Journal of Economic Entomology. 101: 801-809. ra Results and discussion McCornack, B. P., and D. W. Ragsdale. 2006. Efficacy of thiamethoxam to suppress soybean aphid populations in Minnesota soybean. Online. Crop Management doi:10.1094/CM2006-0915-01-RS. Ragsdale, D. W., B. P. McCornack, R. C. Venette, D. A. Potter, E. W. MacRae, E. W. Hodgson, M. E. O’Neal, K. D. Johnson, R. J. O’Neil, C. D. DiFonzo, T. E. Hunt, P. A. Glogoza, and E. M. Cullen. 2007. Economic threshold for soybean aphid (Homoptera: Aphididae). J. Econ. Entomol. 100: 1257-1267. d 138 — 2008 Integrated Crop Management Conference - Iowa State University Schmidt, N. P., M. E. O’Neal, and J. W. Singer. 2007. Alfalfa living mulch advances biological control of soybean aphid. Environ. Entomol. 36: 416-424. 140 — 2008 Integrated Crop Management Conference - Iowa State University Untreated 0 1000 2000 3000 4000 5000 Management of Phytophthora root and stem rot of soybeans Anne E. Dorrance, Associate Professor, Plant Pathology, The Ohio State University Introduction Symptoms ft Historically, Phytophthora root and stem rot is a disease that can cause total losses in yield if the wrong variety is planted in a field with high inoculum and saturated soil conditions develop. There have been sporadic epidemics over the past sixty years, with the highest losses recorded in the late 1960’s and 1970’s. In the past ten years there have been more reports of extensive replanting early in the growing season and higher levels of Phytophthora stem rot later in the growing season. This piece will describe how to recognize this historically important disease but also describe the current management strategies and how to determine when to use fungicide seed treatments. Soybeans are susceptible throughout the growing season to infection from Phytophthora sojae, which causes Phytophthora root and stem rot. Shortly after planting, infected seeds and seedlings will fail to emerge or they will turn a light brown color and die. Many other seedling pathogens will also cause similar symptoms, such as Pythium and Fusarium spp.. When checking stands, these seedlings will appear as dried carcasses or large empty spots. Later in the season, the stem rot phase is much easier to diagnose. A chocolate brown canker which goes from the below ground up the stem is the classic symptom. The tissue inside is discolored. There are cases where the canker may only go up one side of the stem but in all cases, it starts below the soil surface and is continuous. ra Organophosphate (OP) Pyrethroid (PY) 2008 Integrated Crop Management Conference - Iowa State University — 141 This can be easily confused with flooding injury which can occur if plants were submerged by water for a day or more or older plants are in standing water for more than 3 days. With flooding injury, a crust will often form on the soil surface, residue from green algae and a stagnant smell may result from submerged condition. For older plants that are injured, the roots are killed and the outer layer can be easily be pulled off of the root leaving a white “rat tail” appearance. d NI Figure 1. Impact of insecticides on mean aphid exposure and yield. Soybeans were planted on 15 May and insecticides were applied prior to planting to selected plots. The aphid free control was treated with insecticides three times (22 July, 1 August, and 22 August), all other foliar applied insecticides were applied on 1 August. Cumulative aphid days are represented by bars and capital letters. Yields are represented by triangles and lowercase letters. Means with a unique letter are significantly different (P < 0.05). AB E D 1 August 250 @ R6 b Controls b D Aphid free ab DE CruiserMaxx ab Gaucho ab Nicotinoid (NI) Seed Treatments AB A Baythroid XL d Warrior II AB A a a Mustang Max a Hero a Lorsban 4E ab ra NuFos ab ABC ABC Dimethoate ab ABCD Cobalt a AB ft OP + PY ABC Baythroid XL + Lorsban 4E a AB Centric a ABC a Leverage Mean cumulative aphid days (+SEM) 6000 NI + PY 20 25 AB 30 35 40 45 50 55 60 65 a Endigo 70 Mean yield bu per acre (+SEM) Management with host resistance There are two types of resistance used to manage Phytophthora sojae and both have their drawbacks. The most popular are the Rps genes, these are sold in varieties as Rps1a, Rps1c, Rps1k, Rps3 or Rps6. When they work, they are 100% effective and when they don’t work – then the plant has nothing. Due to this “all” or “nothing” type of response, this leads to selection and shifts in the races (pathotypes) that are present in fields. Currently across the Midwest, many fields have populations where Rps1a would not be effective; this is followed by Rps1c and Rps1k. The second type of resistance is partial resistance, also known as field resistance, quantitative resistance and tolerance. In this type of resistance, some disease does develop, the roots are colonized but the stem rot phase never develops. When levels of partial resistance are high in a variety then there are no widespread losses. When the two types of resistance are combined (Rps1c or Rps1k plus high partial resistance), these varieties tend to rank at the top of the yields across years and environments when Phytophthora sojae is yield limiting. 142 — 2008 Integrated Crop Management Conference - Iowa State University ra ft There are really only two active ingredients that have high levels of efficacy towards Phytophthora sojae and they are metalaxyl sold as Allegiance and mefenoxam sold as Apron XL. On the labels there is a range for the rate of the product to be applied to the seed. The low rates of both products, 0.2 fl oz of Allegiance and 0.16 fl oz of Apron XL, are not effective in controlling Phytophthora sojae. The highest rates at 1.5 fl oz Allegiance and 0.64 fl oz of Apron XL have the best control. Seed treatments provide protection from the time of planting until that plant reaches approximately the V1 growth stage. If the proper environmental conditions (saturated soils) do not occur in this time frame, then there will be no benefit from the seed treatment. If saturated soils do occur, then we have had differences of 3 to 30 bu, depending on the length of the saturation period and the susceptibility of the variety. In Ohio, we have seen the greatest benefits in wet springs and in many cases, replanting is totally avoided. For your fields, to assess if a seed treatment could be beneficial here are 3 questions: 1. Has Phytophthora sojae been a problem on this field? 2. Has this field ever had to be replanted as a result of extensive damping-off? 3. Is this field poorly drained? d If you’ve answered yes to all three, then you should see a benefit to using a seed treatment, especially in wet springs. Alison Robertson, Assistant Professor, Plant Pathology, Iowa State University Daren Mueller, Extension Program Specialist, Plant Pathology, Iowa State University Environment plays an important role in disease development, not only in the infection by and growth of the pathogen, but also for the growth and development of the host plant (i.e., corn and soybean crop). As we look back over the past growing season at the weather and diseases that were prevalent, there were few surprise epidemics. ft Seed treatments Review of 2008 growing season from a pathologist’s perspective Temperatures remained below average for most of the growing season so degree day accumulation lagged behind long term averages and resulted in delayed crop growth and development. Northwest Iowa experienced the closest to normal temperatures while southeast Iowa had the greatest deviation from normal temperatures and was very cool (Pope, 2008). The growing season started out wetter than usual. By mid-June, the state had received double the normal precipitation. For the remainder of the growing season, northwest Iowa received below average rainfall. However, for the rest of the state, conditions did not start to dry out until August. In late August, southeast Iowa had another very wet period as a result of Hurricane Ike. All areas except northeast Iowa received rain towards the end of September, when much of the corn across the state reached black layer, and most of the soybeans matured (Pope, 2008). Corn ra Phytophthora sojae is a water mold and it needs saturated soils to form its spore-bearing structures called sporangia. While the soil is still saturated, swimming spores are released from the sporangia and are then attracted to growing soybean roots and germinating seeds. The length of the time the soil is saturated, then serves as the infection period. The shorter the time soils are saturated, then the less time P. sojae has to form sporangia and for the swimming spores to find roots. Both tiling and tillage help to reduce the time that the root zone remains saturated following heavy rains. 2008 Integrated Crop Management Conference - Iowa State University — 143 Common diseases Anthracnose leaf blight was common in corn following corn fields early on in the season. Lesions were found on the bottom 4 to 5 leaves of corn plants. The frequent precipitation that occurred early in the growing season favored inoculum spread and infection. Although midseason diseases such as eyespot, common rust and gray leaf spot (GLS) occurred in many corn fields across the state this growing season, their severity was lower compared with the 2007 growing season. Some might argue that the incidence of common rust (percent of plants within a field with common rust pustules) was greater than in previous years, however the number of pustules on a single leaf plant was low and consequently whole plant disease severity usually never exceeded two percent. Gray leaf spot lesions first occurred on the lower leaves of corn plants towards the end of July, but the unseasonably cool, dry August with low humidity slowed GLS disease development considerably. Anthracnose top dieback was once again a problem in some fields, and anthracnose stalk rot continued to be the predominant stalk rot in Iowa. d Tiling and tillage A number of less common diseases also occurred. (i) Physoderma brown spot Physoderma brown spot is caused by Physoderma maydis, an organism which is closely related to the oomycetes (such as Pythium and the crazy top pathogen). This pathogen overwinters in ra (ii) Goss’s wilt ft In the U.S. this disease is usually of minor importance and consequently resistance is not available (Robertson, et al., 2008; White, 1999). Because the pathogen can survive in infested crop residue, the disease is more common in corn following corn fields particularly if a lot of crop residue remains on the soil surface. Inoculum can be reduced by crop rotation or by reducing surface residue through tillage (Robertson, et al., 2008; White, 1999). Only Headline® lists Physoderma leaf spot on the label; however infections in Iowa are usually not severe enough to warrant a fungicide application. There were numerous reports of Goss’s wilt occurring in Iowa this growing season. Reports of Goss’s wilt came from Boone, Calhoun, Carroll, Cass, Cedar, Chickasaw, Johnson, Keokuk and Pottawattamie (east) counties. There it appears the disease occurred in a band across central Iowa. d Goss’s wilt was first reported on corn in Nebraska almost 40 years ago but since then has been reported across the entire Corn Belt. Even still it is rare to see Goss’s wilt in Iowa. The disease is caused by the bacterium Clavibacter michiganense subsp. nebraskensis. Hosts of the bacterium include corn, green foxtail, barnyard grass and shattercane. Infested corn residue is the major source of inoculum for Goss’s wilt and the bacterium can also be seedborne. Infection of leaves, stems and roots occurs primarily through wounds caused by sandblasting, hail, heavy rain or wind. Corn plants are susceptible at all growth stages (White, 1999). Symptoms of Goss’s wilt that were reported this growing season were leaf blight of the leaves at the top of corn plants, causing many to believe their corn had anthracnose top dieback. Closer examination of plants showed that affected leaves had large gray to reddish or yellow shiny lesions that extended down the leaf veins. Dark green to black “freckles” were evident within the lesions. These “freckles” are diagnostic for the disease. The bacterium also may infect the xylem (water-conducting) tissues of the plant and result in wilting and death of the plants (Robertson, et al., 2008; White, 1999); however, there were no reports of these symptoms. The most effective management tool for Goss’s wilt is to grow a partially resistant hybrid, so check with a seed dealer for hybrids that have resistance to Goss’s wilt. The bacterium is short lived in broken up buried residue so tillage also is helpful. Other management practices include weed management and rotation to non-host crops (White, 1999). There have been concerns raised regarding seed transmission of the bacterium. Work done at ISU in two separate studies showed transmission rate was <0.4% and 0.136%, respectively. Thus seedborne inoculum is of minor concern in an area where the disease is established, but infected seeds could introduce the pathogen into new areas (Biddle et al., 1990). (iii) Southern rust An outbreak of southern rust occurred in Southwestern Iowa, leading to foliar fungicide applications in Taylor county targeted for southern rust. Southern rust is more of a concern than common rust on corn because it is more aggressive, so proper identification is important to make timely fungicide-management decisions. Yield loss due to southern rust, can be severe. In 2006, the disease resulted in yield losses up to 30% in south central Nebraska (Jackson, 2007). Southern rust is favored by warm (77 to 82°F) and humid conditions while common rust is favored by cooler temperatures (Robertson et al., 2008, Jackson, 2007). Symptoms of southern rust are similar to those of common rust with subtle differences. Southern rust pustules are light cinnamon brown to orange and usually circular, ranging in diameter from 0.2 to 2.0 mm. They tend to be densely scattered on upper leaf surfaces and rarely found on the under side of the leaf. Lesions of common rust are larger and more elongated. They are readily found scattered across both the upper and lower surfaces of the leaf. It is possible to have both rusts on the same leaf (Robertson et al., 2008, Jackson, 2007). (iv) Diplodia ear rot ft Symptoms usually appear on mid-canopy leaves. Broad bands of numerous, very small (approximately one-fourth inch in diameter), round to oval, yellowish to brown spots are characteristic of this disease. Dark purplish to black oval spots also occur on the midrib of the leaf. Physoderma brown spot is often misdiagnosed as eyespot or southern rust (Robertson, et al., 2008; White, 1999). 2008 Integrated Crop Management Conference - Iowa State University — 145 Diplodia ear rot was reported from the northeast, central and southeastern parts of Iowa in 2008. The disease was more prevalent this growing season than it has been in recent ears. Fusarium or Gibberella ear rot usually are the most common ear diseases in Iowa. ra infected tissue or soil for up to 3 years and produces numerous zoospores in wet conditions. Corn plants are most susceptible 50-60 days after germination and become more resistant to infection with age. The zoospores of P. maydis infect leaf tissue when free water collects in the whorl and temperatures are between 70-85oF, thus resulting in the bands of infected and noninfected leaf tissue (Robertson, et al., 2008; White, 1999). Diplodia ear rot is caused by the fungus Stenocarpella maydis (Diplodia maydis). The same fungus also causes Diplodia stalk rot. The fungus survives in corn residue and seed, and thus this disease tends to be of a problem in corn following corn fields. Diplodia is rot is favored by cool, wet weather during grain fill. Infection occurs through the silks and/or ear shank, or via the base of the husks of the ear (Robertson, et al., 2008; White, 1999). Symptoms of Diplodia ear rot are a bleached ear leaf and husk. When the husk is peeled back, a dense white to grayish white mold growth that starts at the base of the ear is evident growing between the kernels. Oftentimes the husks of the ear are difficult to remove and appear “glued” to the ear by the mold. Very small, black fruiting bodies called pycnidia can be found scattered on husks or embedded in cob tissues and kernels (Robertson, et al., 2008; White, 1999). d 144 — 2008 Integrated Crop Management Conference - Iowa State University Although S. maydis does not appear to produce mycotoxins in the grain under field conditions usually occurring in Iowa, infected kernels are lightweight and have reduced nutritional value. Damage caused by Diplodia ear rot is usually limited to the field, but the pathogen can be a problem in storage if grain moisture is 20% or above (White, 1999). Options for managing Diplodia ear rot are limited. Rotation out of corn is recommended since the fungus survives in residue. Hybrids do differ in their susceptibility to S. maydis so talk with your seed dealer (Robertson, et al., 2008; White, 1999). Soybean Lots of rain early in the year led to the early establishment of several foliar diseases. Brown spot, bacterial blight, frogeye leaf spot and Cercospora leaf blight (CLB) were reported very early in 146 — 2008 Integrated Crop Management Conference - Iowa State University the season (Figure 1). However, as the season progressed, none of the diseases really became established and caused significant damage. Of these diseases, the two that were most prevalent at the end of the season were brown spot and Cercospora leaf blight. 2008 Integrated Crop Management Conference - Iowa State University — 147 on soybean were given a second chance in 2008. • The two most prevalent diseases seen in Iowa during the 2008 season were brown spot and Cercospora leaf blight. Along with frogeye leaf spot, these diseases all can be managed with a timely application of foliar fungicide. But are disease levels high enough in Iowa to merit a fungicide application? (i) Brown spot With the excessive soil moisture, came the expected root rots and seedling diseases. Phytophthora root rot was more prevalent than any year in recent memory. We will not be covering Phytophthora root rot in this talk. General observations d • Late planted soybean fields had very little foliar diseases. Probably the main reason was that the canopy in these fields never completely closed. Except where Hurricane Ike clipped the southern part of the state, rainfall was normal or even less than normal (Pope, 2008) during the second half of July and August. Drier weather and more open canopies lead to less foliar disease pressure. • If you would have asked me going into the season which of the foliar diseases could potentially cause the most yield loss, my answer would have been frogeye leaf spot. Based on the previous few years, frogeye leaf spot was widespread and severe in certain fields. What was different about the last two years compared to this season? Most likely, frequent rainfall in late July and August in 2006 and 2007. • If it were not for Septoria brown spot, CLB and an occasional field with downy mildew, this would have been a relatively boring year, disease-wise, for soybean. Yes, sudden death syndrome and white mold were seen and brown stem rot was reported in western Iowa, but nothing too bad or exceptional. • One production shift seen was an increase in the number of soybean acres sprayed with a foliar fungicide. Back in 2004, some tried foliar fungicides with decent success. In 2006 and 2007, soybean acreage sprayed with foliar fungicides dropped, as did yield responses to these applications. Because of the market or supposed success with fungicides on corn, fungicides ft A second study was done at the University of Florida, not specifically looking at brown spot, but instead looking at the lower canopy and how it contributes to yield. Two treatments of interest were a fungicide applied to runoff (100% coverage, even in the lower canopy) with and without the lower leaves being physically removed. Similar to the OSU study, lower canopy leaves did contribute to final yield (Mueller et al., 2007). ra ra Figure 1. Brown spot (left) and Cercospora leaf blight (right) found on soybean seedlings in 2008. Two recent studies have suggested that brown spot could be a significant yield nibbler. At Ohio State University, a study was completed in 2007 looking at how brown spot affected yield. Chlorothalonil was applied throughout the season to attain different levels of brown spot. Where brown spot severity was the lowest, final yields were 4 and 2.8 bushels per acre over the nontreated control at two different locations, respectively (Dorrance, 2008). For 2008, brown spot could have been much worse. Some fields, especially in central Iowa, had 100% incidence early in the season. Because of poor canopy closure, the disease did not take over fields, but stayed in the lower canopy until late reproductive stages. Fungicides can be effective at managing brown spot; however, the challenge is always getting the fungicide to the lower canopy. In 2008, some fungicide trials had very little brown spot in the treated areas, which again may trace back to the more open canopies allowing better penetration of fungicides and better management of brown spot. (ii) Cercospora leaf blight Cercospora leaf blight appears in the upper canopy as a purplish cast on the leaves. The infection actually does not occur on the affected leaf, but lower on the plant. The affected leaves are from a phytotoxin produced by the fungus. d ft Brown spot is found in most fields in Iowa, but typically is confined to the lowest part of the canopy. Most growers know about this disease, but don’t give it much thought. Does this disease cause enough damage to matter? We traveled to Louisiana in September to look at soybean rust (yes, I managed to mention soybean rust at least once). We were able to spend the better part of one day with Dr. Ray Schneider, who has been studying CLB for many years. What we learned was quite surprising, and I am still trying to figure how it relates back to Iowa. • The aggressiveness of the fungus seems to have shifted in the past few years. Cultivars that were highly resistant are now susceptible. • CLB is the number one foliar disease in Louisiana, by far. They actually do not even worry too much about soybean rust because all of their fields are getting at least one, often more, application of fungicide targeting CLB. • Despite the targeted foliar fungicides, CLB is still very severe at the end of the season, once the fungicide residual wears off. ft Biddle J.A., McGee, D.C., Braun, E.J. 1990. Seed transmission of Clavibacter michiganense subsp. nebraskense in corn. Plant Disease 74(11):908-911. Dorrance, A. 2008. Illinois Crop Protection Technology Conference. p. 11-14. http://ipm.uiuc. edu/education/proceedings/icptcp2008.pdf Jackson, T. 2007. Rust diseases of corn in Nebraska. NebGuide G1680. Mueller, T.A., Marois, J. J., Wright, D.W., and Mueller, D.S. 2007. Effect of fungicide coverage on control of soybean rust. http://www.plantmanagementnetwork.org/infocenter/topic/ soybeanrust/2007/posters/55.asp ra Pope, R. 2008. A Weather Summary for the 2008 Growing Season. ICMNews. http://www. extension.iastate.edu/CropNews/2008/seasonclimatePope1030.htm Robertson A., Mueller, D. and Tylka G. 2008. Corn diseases (Revised). PM596. Iowa State University Extension. 42pp. d White, D. 1999. Compendium of corn diseases. 3rd edition. APS Press. Increasing the odds of a profitable yield response to foliar fungicide application on corn Alison Robertson, Assistant Professor, Plant Pathology, Iowa State University Introduction During the 2007 growing season, approximately 3 million acres of corn were sprayed with a foliar fungicide. Yield responses due to a fungicide application varied widely. Data compiled from university trials in 12 Corn Belt states and Ontario, Canada in 2007 showed an average yield response of 3 bu/acre to applications of corn fungicides (Bradley, 2008). Among the industries from on-farm trials, BASF reported an average yield increase of 12 to 16 bu/acre, Bayer CropScience an average yield increase of about 10 bu/acre and Syngenta an average yield increase of 15 to 20 bu/acre (Farm Industry News, Feb 15, 2008). ft References 2008 Integrated Crop Management Conference - Iowa State University — 149 During the 2008 growing season, applications of foliar fungicide to corn were again fairly common in Iowa. Early reports of yield responses to a fungicide application once again vary widely. Are we ever going to be able to reasonably predict when a foliar fungicide application could be an economically viable management practice? We know that the fungicides registered on corn are highly effective at reducing foliar disease development. Foliar diseases decrease yield and consequently application of a foliar fungicide protects yield by reducing disease severity. Certain production practices and factors impact the risk of foliar disease. It stands to reason that these practices and factors likely influence response of corn to a foliar fungicide application. ra Despite not seeing as much frogeye leaf spot in Iowa during 2008, CLB was prevalent in many fields by growth stage R5. As far as fungicides for management of CLB, we still have much to learn. What we do know is that strobilurin fungicides are more effective than triazole fungicides (www.sbrfungicides.net). In some of our fungicide studies, CLB severity was reduced with an application of a foliar fungicide at R3. But it still was the most prevalent disease in the upper canopy in both the treated and non-treated plots. Factors that affect the probability of a positive yield response to a foliar fungicide application include: hybrid susceptibility, weather conditions just prior to and during grain fill, disease pressure, cropping history, percent surface residue, yield potential, planting date and geographical location and fungicide application details (timing, technique, carrier volume). Over 30 replicated trials to evaluate the yield response of corn to a foliar fungicide application were completed throughout Iowa from 2006 to 2008. Many of these trials incorporated one or more of the factors listed above that are likely to affect the probability of a positive yield response. Yield data were collected in addition to foliar disease severity at all locations. Stalk rot incidence or severity was collected at approximately 10 of the locations. The influence of these factors on the overall yield response due to each fungicide was determined. d 148 — 2008 Integrated Crop Management Conference - Iowa State University Hybrid susceptibility Yield response to a foliar fungicide varies between hybrids. Since most hybrids vary in their susceptibility to foliar diseases, this is likely no surprise. Bradley’s study (2008) showed the yield response due to a foliar fungicide application was +6 bu/A for hybrids with a “Fair to Poor” rating for gray leaf spot resistance compared with +4 bu/A for hybrids with a “Good to Excellent” gray leaf spot resistance rating. Similarly, Pioneer also reported greater yield responses with hybrids that were susceptible to foliar diseases compared to those that were resistant (Jeschke and Doerge, 2007). No differences were reported in the Iowa state study, likely because disease pressure was low at the experimental sites (Robertson et al., 2007). Similarly in 2008, yield responses to a fungicide application varied widely across hybrids. Fungicide application techniques ft Similarly, at several locations stalk rot severity was lower in fungicide treated plots compared to non-treated plots. Lower stalk rot severity may contribute to improved standability and harvestability. In some studies, a positive yield response was associated with decreased stalk rot disease. Trials were conducted around the state from 2006 to 2008 to determine the optimum time to apply a foliar fungicide and thus attain the most positive yield response. For many trials, the most positive yield response occurred with an application at VT, however there some trials where this was not the case. Previous crop ra Many corn foliar pathogens survive in corn debris and thus when corn was the previous crop and greater than 30 percent residue is left on the soil surface, the risk of foliar disease increases. Trials to compare the average yield response in corn following corn and corn following soybean have not shown a difference in average yield response in Iowa studies (Robertson, 2007; Robertson, unpublished). Jeschke and Doerge (2007) found the average yield response in corn following corn fields was far greater than that in corn following soybean. However, Bradley (2008) found the yield response on corn following soybean was greater than that when corn was the previous crop. Geographical location d Weather conditions across Iowa vary. In southeastern Iowa, mean temperatures in the 80s and humidity above 90 percent during grain fill is the norm. In northwest Iowa, conditions are usually cooler and drier. As a result, foliar disease pressure, particularly gray leaf spot, is often greater in the southeastern part of the state compared with the northwestern part. With this in mind, yield response to a foliar fungicide on corn would be expected to be more positive in the southeastern cropping district versus the northwestern cropping district. Data from corn foliar fungicide trials conducted at ISU research and demonstration farms around the state have not necessarily reflected this difference. Summary Foliar fungicides remain an effective disease management tool. Positive yield responses can occur when disease pressure is low. Factors that impact the profitability of positive yield response to a foliar fungicide application are many, and complex interactions between two or more factors likely occur and may further confound the issue. Determining the hierarchy of factors that are important will require an exhaustive compilation of all data (disease pressure, production practices, and fungicide application details) from many sites over several years. Until we have a better understanding of what these risk factors are, yield benefits from a fungicide application on corn should be determined on an individual basis, grower by grower, field by field and year by year. References Bradley, C. 2007. Summary of university trials on foliar fungicide applications on corn. NCDC 214 Meeting, Chicago, IL, Dec 5, 2008. Jeschke, M., and Doerge, T. 2007. Management of foliar diseases in corn with fungicides. Pioneer Crop Insights 17(14):1-4. Robertson, A., Abendroth, L., and Elmore, R. 2007. Yield responsiveness of corn to foliar fungicide application in Iowa. Integrated Crop Management IC-498(26):281-285. ft Foliar disease pressure was extremely low throughout the state in 2008. In southeast Iowa, the gray leaf spot haven of Iowa, gray leaf spot severity on the ear leaf averaged <5% at growth stage R5. Fungicides reduced severity of disease at all locations tested and all fungicides registered for use on corn were equally effective. Similar to 2007, at some locations a corresponding positive yield response occurred. 2008 Integrated Crop Management Conference - Iowa State University — 151 ra Disease pressure d 150 — 2008 Integrated Crop Management Conference - Iowa State University 152 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 153 Use of fungicides to control soybean foliar diseases in Iowa: a 6-year summary XB Yang, Professor, Plant Pathology, Iowa State University S.S. Navi, Assistant Scientist, Plant Pathology, Iowa State University Ken Pecinovsky, Farm Superintendent, Northeast Research Farm, Iowa State University Introduction ra ft Prior to the 2004, foliar diseases were not a concerned in soybean production in Iowa and much of the north central region, except for soybean seed production. Since the report of Asian soybean rust, caused by Phakopsora pachyrhizhi, in South America in 2001 and then in the United States in 2004, fungicide applications became of interested in some producers. Such interest increased recently as soybean price increase. Use of fungicides to control soybean foliar diseases has been a hot topic. Survey of the literature shows a disagreement among researchers, between university extension recommendations and industry application. Among university researchers, there are disagreements. Since 1993, we have tested various fungicides on the requests of chemical companies to optimize dose and application times. Their treatments varied in chemical compounds, chemical dose, and timing of application. In some seasons, over 50 treatments were tested in multiple locations with 4 replications for each treatment. In each year, the fungicide trials comprising several fungicides from following companies: Entries from chemical companies vary from year to year and the soybean varieties planted also varied from year to year. The experiments were established at the ISU research farms at different locations such as Northeast Research Station, in Nashua, IA. On farm testing was also conducted in some years. In each experiment, a typical plot consisted of eight rows, with four rows unsprayed border. Rows in plots were 30 inch apart. A randomized complete block design with four replications was used. Plot yields (bu/ac), the incidence (%) and severity (%) of foliar diseases and white mold were recorded. d d ra ft John Shriver, Research Associate, Plant Pathology, Iowa State University We summarized the fungicide efficacy mainly use our data collected over the last 6 years. In the meantime, we consult strip trial data published by On Farm Network of Iowa Soybean Association. We also reference data published by our colleagues in other laboratories at ISU. This article details the efficacy of individual fungicides on fungal foliar diseases of soybean. The results are presented in two sections. The first section provides general findings and recommendation. The second section gives detailed data of each season, and discussed results which help pick up individual chemicals. Finally, we discuss how to make spray decision during a growing season. General findings Table 1 is the master table which summarizes the 6 year results by ranking no-spray check treatment with all treatments tested. Our results clearly showed that use of fungicide as a preventative measure can increase yields in a season when disease pressure is moderate or high. 154 — 2008 Integrated Crop Management Conference - Iowa State University In such a season, most fungicide treatments yielded better and a few treatments increased yield over 10 bushels. In seasons with a low disease pressure, only a few treatments, which had right chemicals and were made at a right time, consistently produced higher yields. Specially, below are major findings: 1. There are treatments consistently ranked top in terms of increase in yields in our multiple year tests (except for one season) even when disease pressure was low to moderate. 2. Application at R1 or earlier did not pay off, except for the Cobra which is to control white mold. 3. Application at R3 consistently produced highest yields. 4. Application twice in a season was no better than a single application at R3. Reference from other states: spray efficacy is location specific and vary from year to year. Data from other states have little use to guide sprays in Iowa. One good example is used Cobra to control white mold. The chemical is effectively used by many producers in Iowa. The method, however, did not work in research plots in states where soil fertilities are low. Nashua 2 8 Low to Moderate 35.7–46.4 39.7 3 Nashua 3 14 Low to Moderate 54.3–60.1 57.4 10 ft 2003 Fungicides are for the seasons when foliar diseases are severe. Correct assessment of potential disease pressure is a key to make a good decision. When disease is prevalent and severe in a season, application of fungicide is more likely to increase yields. The higher the foliar diseases severity was, the greater the return from the use of fungicide applications. However, the disease risk is a critical factor in making spray decision but may not be the only factor. There are compounds which seem to boost yields even disease was low. Currently, no forecasts are available to predict foliar disease risk and most recommendations are made based on the precipitation in a growing season. Below are the conditions which may help in deciding fungicide application and may likely to pay off financially IF: ra ft Treatment yield range Bu/ac ra Year 1. the season is wetter than normal 2. soybean fields have high yield potential 3. sprayed at R3 growth stage 4. a right chemical is selected. Nashua – 1 4 18 Low to Moderate 68.4–76.3 68.1 1 Nashua – 2 5 27 Low to Moderate 71.6–78.5 71.6 1 Crawfordsville 6 22 Low to Moderate 59.8–71.8 65.2 10 2006 Nashua –1 7 7 Low to High 52.5–62.3 52.5 1 Results and analysis by year 2006 Nashua – 2 8 12 Low to High 55.4–63.3 63.3 11 2003 Summary (Table 2) 2006 Nashua 9 24 Low to High 68.5–77.1 71.6 5 2007 Nashua – 2 spacing trial 10 8 Low to High 62.6–66.0 64.5 4 2007 Ames, (Curtiss farm) 11 27 Low to High 35.8–39.3 37.4 11 2007 Newhall-Grower 12 8 Low 75.5–87.15 79.2 4 2008 Nashua 13 22 Low to Moderate 56.0–65.3 56.8 5 2008 Ames, (Agronomy farm) 14 13 Low to Moderate 39.0–46.8 41.7 4 2005 d 2005 d 2005 Overall foliar* disease severity No spray check yield Rank** Bu/ac for check Experiment location 2004 Number of Treatments For years, Cobra has been used to control white mold in eastern Iowa. In recent years, efforts have been made to use Cobra to manage foliar diseases. Our results showed that Cobra is effective in reducing white mold but not effective to control foliar diseases. In the absence of white mold, untreated control had yielded 2 bushels higher than the control. Cobra, which is a herbicide, remains effective only to white mold. When to make spray decision? Table 1. Summary of fungicide trials conducted at Northeast Research and Demonstration Farm, Nashua, Southeast Research and Demonstration Farm, Crawfordsville and Central Iowa Research and Demonstration Farms (Hinds, Curtis, and Agronomy) Ames, IA, during 2003-2008 Table No. 2008 Integrated Crop Management Conference - Iowa State University — 155 This year was the first year we tested soybean foliar fungicides after soybean rust was reported in South America. Only BASF requested the test for their product. Objectives were to determine the number of spray and time of spray. Conclusion: Treatments of Headline applied at R3 had best economical return. 2004 Summary (Table 3). Objectives were to determine: 1) spray time, 2) number of sprays, 3) and efficacy when used with insecticides. However, this year white mold were very severe, which produced unwanted results. * = Bacterial leaf blight, Brown spot, Downy mildew, Frogeye leaf spot, and white mold. Conclusions: Spray earlier before reproductive stage did pay; 2) Headline had no control on white mold; 3) Fungicide treatments having insecticide did pay off economically. Low = 0–10, Moderate = 11–20 and High = >21%. 1= data not presented. 2005 Summary (Tables 4 to 6). ** Yield rank is in ascending order, the smaller the number in the rank, the lower the yield. This was the first season after soybean rust was reported in the United States. Many chemical 156 — 2008 Integrated Crop Management Conference - Iowa State University companies requested to test their products. Large set experiments were conducted by different laboratory at Iowa State University. 2008 Integrated Crop Management Conference - Iowa State University — 157 Table 2. A 2003 Soybean disease control / yield response study, Northeast Research and demonstration farm, Nashua, IA Conclusions: Cercospora leaf spot Application rate oz/acre Application timing Incidence % Severity % Yield Bu/acre - Treatment with one spray did not have significant difference from these having two sprays. Products tested - Sprays at R2 and R3 had the best results. Quadris 9.2 R3 17.5 15 35.7 Headline 9.2 R5 3.3 2 38.4 14.3 11.7 39.7 2006 Summary (Tables 7 to 9) Conclusion: ft 2006 data were originally published in an article in ISU ICM Newsletter (1). We reanalyzed the published data and ranked the treatments by yield. What we found are as below: - Foliar diseases were prevalent and severe in Trial 1, but very low in Trials 2 and 3. - Increase of 5–7 bushels in yield occurred in treated plots of Trial 1 which had severe diseases. - In Trial 2, there were no yield increases due to low disease incidence except for 2 treatments. ra - In Trial 3, generally there was yield increase of 2-3 bushels in treatments with Headline despite of light disease in these plots. Untreated check 0 Headline 9.2 R3 and R5 7.5 4 42.6 Headline 9.2 R3 11 15 43.2 Headline 6.14 R3 2.7 1 43.7 Headline 12.3 R3 7.7 7.3 45.7 Headline 6.14 R3and R5 8.3 4 46.4 ft - Treatments with one chemical or mixture of two or more chemicals had similar effects on disease control and yield increase. Table 3. A 2004 Soybean disease control / yield response study, Northeast Research and demonstration farm, Nashua, IA Products tested Application rate (fl.oz) Application time Mean* Severity (%) White mold Brown spot Yield Bu/ac 6.14 R3-R5 11.8 12.5 54.3 Conclusion: Headline with NIS 3.07 V5/R1-R2 31.3 7.5 55.0 - There were no significant differences between unsprayed and sprayed treatments. Headline with NIS 6.14 V5 13.8 8.8 55.5 - The yields were in the range of high 30 bushels per acre, not high. Headline with NIS 6.14 R1-R2 23.8 7.5 55.8 - Spray did not pay off in this experiment because of small margins of yield differences although 2007 growing season was. Headline with NIS and Lorsban 6.14 R3-R5 2.5 22.5 56.3 Headline with NIS+Warrior 6.14/3.2 R3-R5 10.5 12.5 56.8 2008 Summary (Tables 13 to 14) Headline with NIS 3.07 V5 26.3 13.8 57.1 To determine the effects of various fungicides in while mold control. 2008 season had moderate white mold and other foliar fungal diseases. Warrior insecticide only 3.2 R3-R5 5.5 12.5 57.2 Headline with NIS 3.07 R1-R2 26.3 15 57.3 Unsprayed check 0 N/A 10.8 16.3 57.4 Headline with NIS 6.14 R3-R5 12.5 10 57.4 V5 25 12.5 58.0 6.14/3.2 R3-R5 12.8 11.5 59.0 6.14/4 R3-R5 14.5 8.8 60.1 - Sprays at R1 did not increase yield except for treatment with Endura - Cobra applied at R1 increased yield because white mold pressure was high - Headline increased yield when applied at R3 growth stage. However, this should not say it controls while mold because application was made at R3 when infections already took place. Increase in yield by Headline was likely the results of controlling other foliar diseases and undetermined physiological response. d Conclusion: ra Quadris abound with NIS d 2007 Summary (Tables 10 to 12) Headline with NIS Quadris abound with NIS + Warrior Headline with NIS + Mustang Max 158 — 2008 Integrated Crop Management Conference - Iowa State University White mold inc % White mold sev % Yield Bu/ac Untreated check 0 0 20.0 2.3 35.0 68.34 Domark / Quadris 0.071/0.05 lb R1 / R5 11.7 0.0 0.0 69.58 Domark 0.09 lb ai/acre R1 / R5 13.3 0.0 0.0 70.08 Domark / Flint 0.071/0.062 lb R1 / R5 13.3 0.0 0.0 70.10 Domark / Flint 0.071/0.081 lb R1 / R5 13.3 0.0 0.0 70.19 Domark / Headline 0.071/0.097 lb R1 / R5 8.3 0.0 0.0 70.20 Headline / V-10116 0.076/0.08 lb R1 / R5 3.7 1.0 11.7 70.91 Tilt / Flint 0.081/0.081 lb R1 / R5 15.0 1.0 28.3 71.03 Domark / Quadris 0.071/0.065 lb R1 / R5 16.7 0.0 0.0 71.13 Quadris 0.1 lb ai/acre R1 / R5 13.0 0.0 0.0 71.17 Domark / V-10171 0.071/0.13 lb R1 / R5 10.0 0.0 0.0 71.49 Headline / Folicur 0.076/0.088 lb R1 / R5 11.7 0.0 0.0 71.55 Tilt / Quadris 0.163/0.097 lb R1 / R5 20.0 0.0 0.0 72.48 0.071/0.1 lb R1 / R5 23.3 1.0 18.3 72.50 Headline 0.15 lb ai/acre R1 / R5 13.3 0.0 0.0 73.78 Flint 0.125 lb ai/acre R1 / R5 10.0 1.3 21.7 74.34 Domark / Headline 0.071/0.074 lb R1 / R5 8.3 0.0 0.0 75.78 V-10171 0.2 lb ai/acre R1 / R5 18.3 0.0 0.0 76.35 ra Domark / V-10171 d Design: RCBD; Variety Planted: S24-K4 RR; Plant population: 196,433 /ac; Row spacing: 30 inch, Plot size: 10 ft wide and 30 ft long. Mean of 4 replications. BS Sev % 18.4 11.3 15.0 11.3 7.5 10.0 12.5 WM inc % 1.5 1.0 2.0 0.0 1.8 0.0 1.5 WM Sev % 70.0 70.0 70.0 0.0 66.3 0.0 68.8 Phtyotoxicity 0 0 0 0 0 0 0 Yield bu/ ac 71.59 72.71 72.71 72.72 72.99 73.01 73.24 Products tested Application Rate Application time Untreated check 0 N/A Domark 5 oz/ac R3 Folicur + Folicur 4+4 oz/ac <=10%Rust/7-10d Heads Up 1g/L Of Spray 1st True Leaves Folicur + Folicur 3.56+3.56 oz/ac R1/21d Echo + Echo 20+20 oz/ac V5+R3 Caramba + Headline/ 6.1+3.6/6.1+3.6 oz/ac R2/21d If Rust Caramba + Headline Echo + Folicur 20+4 oz/ac V5+R3 6.3 1.3 67.5 0 73.44 Headline + Folicur/ 4.71+3.16/4.71+3.16 R1/21d 16.3 2.0 63.8 0 74.01 Headline + Folicur oz/ac Dithane 2.5 lbs/ac R5 12.5 1.3 65.0 0 74.17 Impact +Impact 7+7 oz/ac R1/28d 10.0 0.0 0.0 0 74.26 Caramba + Headline/ 3.2+4.7/3.2+4.7 oz/ac R2/21d If Rust 10.0 1.5 67.5 0 74.70 Caramba +Headline Folicur + Folicur 4+4 oz/ac R1/R5 16.3 1.3 68.8 0 74.72 Impact + Impact 7+7 oz/ac R1/18-20d 15.0 0.0 0.0 0 74.76 Caramba + Headline/ 9.6+4.29/9.6+4.29 oz/ac R1/21d 7.5 1.5 68.8 0 74.95 Caramba + Headline Caramba + Headline/ 7.68+4.43/7.68+4.43 R1/21d 20.0 2.5 61.3 0 74.96 Caramba + Headline oz/ac Domark + Domark 3+3 oz/ac R1+ R5 5.0 1.0 66.3 0 75.14 Headline/Headline + 6/4.71+3.16 oz/ac R4/21d If Rust 12.5 1.5 65.0 0 75.72 Folicur Headline/Headline + 6.14/4.43+7.68 oz/ac R1/21d 10.0 1.8 62.5 0 76.03 Caramba Caramba + Caramba 9.6+9.6 oz/ac R1/21d 11.3 1.0 67.5 0 76.04 Headline/Headline + 6.14/4.71+3.16 oz/ac R1/21d 6.3 0.0 0.0 0 76.62 Folicur Domark + Domark 4+4 oz/ac R1+ R5 10.0 1.8 67.5 0 76.72 Caramba + Headline/ 7.7+4.4/7.7+4.4 oz/ac R2/21d If Rust 8.8 1.0 70.0 0 76.97 Caramba + Headline Headline/Headline + 6/4.71+3.16 oz/ac R2/21d If Rust 13.8 1.5 65.0 0 77.39 Folicur Headline 6 Oz/ac R3 6.3 1.3 68.8 0 77.72 Caramba + Headline/ 2.38+3.6/2.38+3.6 oz/ac R2/21d If Rust 10.0 1.8 62.5 0 78.02 Caramba + Headline Headline/Headline + 6/4.71+3.16 oz/ac R3/21d If Rust 12.5 1.8 70.0 0 78.54 Folicur Note: Out of 45 treatments results of 27 treatments are listed above. Design: RCBD; Variety Planted: 92B32 RR; Plant population: 196,433 /ac; Row spacing: 30 inch, Plot size: 10 ft wide and 30 ft long. Mean of 4 replications. BS=Brown spot, WM=White mold ft Brown spot sev % ra Application time ft Products tested Application Rate Table 5. Evaluation of fungicides for use against soybean foliar diseases and white mold during 2005 at Northeast Research and demonstration farm, Nashua. d Table 4. Evaluation of fungicides (a set 18 treatments) for use against soybean foliar diseases and white mold during 2005, Northeast Research and demonstration farm, Nashua, IA 2008 Integrated Crop Management Conference - Iowa State University — 159 160 — 2008 Integrated Crop Management Conference - Iowa State University Frogeye Sev % Phytotoxicity (%) Yield bu/ac R1/18 to 21 DAPS 6.3 5.0 1.3 59.78 R3 6.3 7.3 0.0 63.30 6.3 4.3 2.5 63.36 R1 See Note 8.8 8.8 7.5 63.49 R1 6.3 1.8 0.0 63.54 6.3 8.8 0.0 63.58 See note 7.5 7.5 0.0 64.34 First true leaves 8.8 15.0 0.0 64.82 5.0 6.8 0.0 64.82 10.0 20.0 0.0 65.26 7.5 4.3 0.0 66.21 R1/R5 6.3 5.0 0.0 66.32 R3 7.5 3.0 0.0 66.42 10 Domark 5 Quilt 14 Caramba 9.6 Punch 4 A12910 4 Folicur 4 1g/L of spray Heads Up A9901 1.03 0 Tilt 4 N/A ra Untreated check ft Impact Products tested Domark 4 Headline Inc% Sev% Inc% Sev% Inc% Sev% Bu/ac Untreated check 0 N/A 88.8 43.8 78.8 27.5 0.43 62 52.49 Topguard 7 R3 75 25 80 33.8 0.68 50 55.44 Topguard 14 R3 100 52.5 100 25 0.3 75 56.88 7, 0.25% v/v R3 75 40 80 30 0.31 50 57.63 7, 6 R3 100 42.5 100 30 0.28 50 58.66 Spectra 4 R3 Topguard 7 R3/R5 Product tested Topguard/NIS Topguard/ Headline 32.5 0.69 75 59.25 90 35 90 25 0.48 75 62.25 Inc% Sev% Yield Bu/ac R3/R5 0 0 0 0 2.18 100 55.35 2 R3/R5 0 0 0 0 1.37 100 56.18 5 R3 0 0 0 0 1.63 100 57.56 4 R3/R5 0 0 0 0 1.65 100 58.17 LEM 17/Folicur 2, 2 R3/R5 0 0 0 0 0.83 100 58.42 LEM 17 3.5 R3/R5 0 0 0 0 1.94 100 58.91 4 R3 0 0 0 0 1.96 100 59.20 3, 3 R3 0 0 0 0 1.48 100 59.93 5 R3 0 0 0 0 1.66 100 60.28 2, 3.3 R3/R5 0 0 0 0 1.88 100 62.58 0 0 0 0 2.44 100 63.23 0 0 0 0 1.20 100 63.33 Folicur 4 R1 7.5 15.0 0.0 67.51 LEM 17 Impact 7 R1/28 DAPS 6.3 2.3 0.0 69.02 LEM 17 7.68 + 4.43 R1 See Note 7.5 2.3 1.3 69.69 LEM 17 Folicur 3.56 R1 See Note 6.3 3.0 0.0 70.10 Headline 6.14 R1 See Note 5.0 1.3 1.3 70.73 4.71 + 3.16 R1 See Note 3.5 1.5 0.0 70.73 6.14 R1 See Note 4.3 6.8 1.3 71.07 9.6 + 4.29 R1 See Note 6.8 3.0 0.0 71.81 d Punch 5 White mold Sev% Product tested Application Time Frogeye leaf spot Inc% 67.26 Application rate (oz / ac) Downy mildew Sev% 0.0 d 77.5 Inc% 1.8 Note: Out of 38 treatments, results of 22 treatments are listed above. Design: RCBD; Variety Planted: Pioneer 93M42; Plant population: 160,000/ac; Row spacing: 30 inch, Plot size: 10 ft wide and 35 ft long. Mean of 4 replications. 45 Table 8. Evaluation of fungicides for use against soybean foliar diseases and white mold during 2006 at Northeast Research and demonstration farm, Nashua, IA (Expt 2) 8.8 Caramba + Headline 100 Note: Out of 22 treatments, results of 7 treatments are listed above. Design: RCBD; Variety Planted: Asgrow 2106RR; Plant population: 196,433/ac; Row spacing: 30 inch, Plot size: 10 ft wide and 30 ft long, Mean of 4 replications. R1/R5 Headline Yield Application Time 3 Headline + Folicur White mold Application rate (oz / ac) Domark Caramba + Headline Frogeye leaf spot Downy mildew ft Brown spot Sev % Application Time Table 7. Evaluation of fungicides for use against soybean foliar diseases and white mold during 2006 at Northeast Research and demonstration farm, Nashua, IA (Expt 1) ra Table 6. Evaluation of fungicides (a set 38 treatments) for use against soybean foliar diseases and white mold during 2005 at Southeast Research and demonstration farm, Crawfordsville, IA Application rate (floz/ac) 2008 Integrated Crop Management Conference - Iowa State University — 161 Domark Domark/Quadris Phenix LEM 17/Punch Untreated check 0 Headline 6 R3 Note: Out of 20 treatments, results of 12 treatments are listed above. Design: RCBD; Variety Planted: 92M40RR; Plant population: 196,433 plants/ac; Row spacing: 30 inch; Plot size: 10 ft wide and 30 ft long. Mean of 4 replications. 162 — 2008 Integrated Crop Management Conference - Iowa State University Table 9. Evaluation of fungicides for use against soybean foliar diseases and white mold during 2006 at Northeast Research and demonstration farm, Nashua, IA (Expt 3) Application rate Application Time White mold Sev% 30 in row Avg yld bu/ac 10 in row Avg yld bu/ac Endura 10oz R1-R2 Moderate 62.65 66.83 Cobra 6 oz R1-R2 Moderate 63.50 64.96 Inc% 0 Sev% 0 Inc% 0 Sev% 0 Inc% 0.94 Sev% 87.5 R3 0 0 0 0 0.89 87.5 69.55 Endura 5.5oz R1-R2 Moderate 64.23 64.58 3.6 + 6.1 R3 0 0 0 0 0.83 87.5 69.90 Untreated check 0 0 Moderate 64.48 64.97 8.2 R3 0 0 0 0 1.33 85 71.03 6+5.5oz R1-R2 Moderate 65.21 63.36 Untreated check 0 N/A 0 0 0 0 1.33 67.5 71.69 Headline + Endura Headline + NIS, Headline + Caramba Stratego 6 + 0.25% v/v, 3.6 + 6.1 R3 0 0 0 0 1.16 90 71.88 Headline 6 oz/A R3 Moderate 65.67 67.88 Headline 6 oz/A R1 Moderate 65.82 68.26 7 R3 0 0 0 0 1.77 85 72.20 Endura / Headline 6 oz R1+R3 Moderate 66.06 67.49 2.88 + 3.1 R3 0 0 0 0 1.64 87.5 72.23 Domark 5 R3 0 0 0 0 1.7 87.5 72.25 Quilt 14 R3 0 0 0 0 1.95 85 72.25 6 + 0.125% v/v R3 0 0 0 0 1.66 85 72.38 4 R3 0 0 0 0 1.31 87.5 72.55 6.2 + 0.125% v/v 4.7 + 3.2 R3 0 0 0 0 0.42 65 72.73 R3 0 0 0 0 1.1 87.5 73.33 4.4 + 7.7 R3 0 0 0 0 1.83 88.8 73.53 4.4+7.7/3.1+6.1 R3 0 0 0 0 0.73 87.5 73.53 3.6 + 2.4 R3 0 0 0 0 0.64 90 73.85 4.4 + 7.7 R3 0 0 0 0 1.15 81.3 74.08 6 / 3.1 + 6.1 R3 0 0 0 0 0.69 67.5 74.23 6, 0.25% v/v R3 0 0 0 0 0.42 87.5 74.60 Headline + Caramba (12.1) Headline 4.4 + 7.7 R3 0 0 0 0 1.54 87.5 74.78 6 R3 0 0 0 0 0.71 92.5 75.60 Headline SBR 7.8 R3 0 0 0 0 1.33 87.5 75.63 0 0.75 92.5 77.05 Products tested Laredo ra Gem + Folicur Headline + NIS Folicur Quadris + NIS d Headline + Folicur Headline + Caramba (12.1) HL/Caramba (12.1)/HL/ Caramba (9.7) Headline + Folicur Headline + Caramba Headline/ Headline + Caramba (9.7) Headline + NIS Headline + 4.4+7.7 / 8.2 R3 0 0 0 Caramba (12.1)/ Caramba Design: RCBD; Variety Planted: 92M91RR; Plant population: 196,433 plants/ac; Row spacing: 30 inch; Plot size: 10 ft wide and 30 ft long. Mean of 4 replications. ft 6+ 0.25% v/v, 8 Products tested Yield bu/a 68.50 Note: Data sorted on 30 inch row spacing, Mean of 4 replications ra Headline + NIS, Caramba Headline + Caramba Caramba White mold Table 10. Evaluation of fungicides for use against soybean foliar diseases during 2007 at Northwest Research and demonstration farm, Nashua, IA d Application Time R3 Frogeye leaf spot ft Application rate (oz / ac) 7 Downy mildew 2008 Integrated Crop Management Conference - Iowa State University — 163 164 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 165 Table 11. Evaluation of fungicides for use against soybean foliar diseases and white mold during 2007 at Central Research and Demonstration Farm (Curtiss Farm), Ames, IA Application timing Brown spot Incidence (%) Brown spot Severity (%) Yield Bu/ac Table 12. Evaluation of fungicides for use against soybean foliar diseases and white mold during 2007 at Newhall (grower’s field), IA Products tested Application Rate Headline/Nis 6 fl oz/0.25 Application time White mold Inc% Yield Bu/ac R3 0 75.50 Punch 3 fl oz R3 71.3 5.0 35.8 Headline/Endura/NIS 6 fl oz/5.5 oz/0.25 R1-R2 0 75.73 Orthene + Cobra + NIS 1lb+6 fl oz+0.25% R3 95.0 17.5 36.0 Headline/Nis 6 fl oz/0.25 R1-R2 0 77.71 A12910 + NIS 6.5 fl oz + 0.25% R3 65.0 6.3 36.1 Untreated check 0 N/A 0 80.20 Folicur 4 fl oz R2 70.0 6.3 36.2 Endura/NISHeadline/NIS 5.5 fl oz/0.25/6/0.25 R1/R3 0 80.85 Topguard 14 fl oz R2 80.0 5.0 36.3 Endura/NIS 10 oz/0.25 R1-R2 0 81.50 Absolute 5 fl oz 0 85.95 Evito + NIS 3.1 + .25% Topguard 7 fl oz Domark 3 fl oz Folicur 4 fl oz Untreated check 0 Punch + Headline 3 fl oz + 4.5 fl oz R2 71.3 6.3 36.8 Cobra R1 & R3 62.5 6.3 36.9 Endura/NIS R2 68.8 6.3 36.9 R3 57.5 5.0 37.0 R2 60.0 5.0 37.2 77.5 6.3 37.4 67.5 6.3 37.7 ra R3 5.5 oz/a/0.25 ft Application Rate ft Products tetsted R1-R2 0 87.15 Table 13. Evaluation of fungicides for use against soybean foliar diseases and white mold during 2008 at Northeast Research and demonstration farm, Nashua, IA Application rate Application time WM Inc% WM Sev% FELS Sev BS Sev BLB Sev Bu/ac 5.5 oz R1 0.9 13.8 L L VL 56.04 82.5 6.3 37.7 R2 &R4 66.3 6.3 37.9 Endura 6 fl oz + 4 fl oz + 0.25% R3 67.5 5.0 37.9 Headline+Endura 6+5.5 oz R1 2.0 26.3 L L VL 56.11 Headline 6 oz R1 1.0 20.0 L L VL 56.54 Domark + orthene + Lorsban 3 fl oz+0.75 lb+4 fl oz R3 62.5 6.3 38.0 Quadris 6 oz R3 1.4 20.0 L L VL 56.98 Domark 4 floz R3 71.3 6.3 38.0 1.2 25.9 L L VL 57.07 Domark + orthene + Lorsban 4 fl oz+0.75 lb+4 fl oz R3 67.5 7.5 38.5 A12910 + NIS 6.5 fl oz + 0.25% R3 82.5 6.3 39.2 Evito + NIS 3.1 + .25% R1 & R3 71.3 7.5 39.3 Quilt + COC 14 fl oz + 1 R3 70.0 6.3 39.3 Topguard 7 floz Quaris + Alto + NIS Untreated Check 0 Tebuzol 4 oz R3 2.1 20.0 L L VL 57.16 10 oz R1 0.9 18.8 L L VL 57.59 16 oz R3 1.6 20.0 L L VL 58.31 Topsin + Tebuzol 16+4 oz R3 1.5 20.0 L L VL 58.88 Cobra 6 oz R1 0.4 21.3 L L VL 59.07 Endura/Headline 5.5/6 oz R1/R3 0.7 11.3 L L VL 59.14 Headline 6 oz R3 1.3 21.3 L L VL 59.86 Topsin Xtr 20 oz R3 1.5 18.8 L L VL 60.47 Headline 6 oz R3 1.7 20.0 L L VL 62.02 Headline+Respect 6+3.2 oz R3 1.3 17.5 L L VL 65.31 Endura Topsin d 10 fl oz + 0.125% d Stratego + Induce ra R2 Products tested Design: RCBD; Variety Planted: 92M76RR; Plant population: 210,000/ac; Row spacing: 10 inch; Plot size: 20 ft wide and 50 ft long. Mean of 4 replications 166 — 2008 Integrated Crop Management Conference - Iowa State University Application rate fl oz/ac Application Time BS-Sev% BLB Sev% Yield Bu/ac Topguard 7 R1-R2/R3-R4 18.7 <5 39.0 Topguard 7 R1-R2 12.5 <5 40.4 Folicur 4 R1-R2 15.0 <5 41.3 Untreated 0 19.6 <5 41.7 Products tested 2+0.25%NIS R1-R3/21DAPS 12.5 <5 42.9 14 R1-R2 7.5 <5 43.2 3+0.25%NIS R1-R3/21DAPS 16.25 <5 43.2 Tebuzol 4 R3 10.0 <5 43.3 Topsin 16 R3 10.0 <5 43.9 KFD 21-03 20 R3 7.5 <5 46.0 R3 7.5 <5 46.8 Topguard Evito 480SC Topsin/Tebuzol 16 / 4 ft Evito 480SC L. Leandro, X.B. Yang, A. Robertson, S.S. Navi, and J. Shriver. 2006. Evaluation of Soybean Fungicides in 2006. Iowa State University, Northeast Research, and Demonstration Farm ISRF06-13 X.B. Yang, S.S. Navi, and K. Pecinovsky 2005. Evaluation of fungicides for the control of Cercospora Leaf Spot, white mold, and brown spot of soybean. Iowa State University, Northeast Research, and Demonstration Farm ISRF04-13 ft Table 14. Evaluation of fungicides for use against soybean foliar diseases during 2008 at Central Research and Demonstration Farm (Agronomy Farm), Ames/Boone, IA d Because of the page limitation of this proceeding, we are unable to list all the results and if any one would like to have copies of the tables, one can obtain by sending a request to xbyang@iastate.edu. References Iowa Soybean Association. Can Fungicides Boost Profits In Iowa? http://www.siue.edu/ stalknitrate/ Iowa Soybean Association. 2005. 2004 Soybean Fungicide and Foliar Feeding Trials. ttp:// www.isafarmnet.com/fungicide/page1.pdf Iowa Soybean Association. 2006. Soybean Fungicides 2005 Strip Trial Results. http://www. isafarmnet.com/06Nconf.html A. Robertson, J. Shriver, S.S. Navi, and X. B. Yang. 2006. 2005 trials: Efficacy of soybean rust fungicides on other fungal diseases in Iowa IC-496(3):46-47. ra Thanks are given to Mark Carlton for suggestions and questions over the years, to Allison Robertson and Leonor Leandro for discussion. We thank Arysta LifeSciences, BASF Corporation, Bayer CropScience, Cheminova Inc., Dow AgroSciences, DuPont, HeadsUp, Shaeffer, Syngenta Crop Protection, United Phosphorus Inc. and Valent USA for product support during these years. d ra Design: RCBD; Variety Planted: Pioneer 92M61; Plant population: 150,000/ac; Row spacing: 30 inch; Plot size: 10 ft wide and 30 ft long. Mean of 4 replications. Acknowledgements 2008 Integrated Crop Management Conference - Iowa State University — 167 168 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 169 Glyphosate-resistant waterhemp: Lessons learned from the devastation resistant palmer amaranth has had on southern agriculture Jason K. Norsworthy, Associate Professor, Weed Science, University of Arkansas · its level of resistance, · differences in resistant biotypes, · extent of resistance, ft Palmer amaranth has become increasingly prevalent in crop fields in the southern U.S. over the past 8 to 10 years. Glyphosate resistance in Palmer amaranth was first confirmed in Georgia in 2004. Now, glyphosate-resistant Palmer amaranth is widespread in Georgia, Arkansas, Tennessee, North Carolina, South Carolina, Tennessee, and Mississippi. The resistant biotype is causing substantial yield loss, reduction in harvest efficiency, and complete abandonment of some fields. The focus of this presentation will be on glyphosate-resistant Palmer amaranth, a close relative of waterhemp, including: ra · likely factors that have contributed to evolution of resistance, · pollen and seed dispersal as a means for gene flow (resistance movement), · its impact on southern agriculture, and · potential alternatives and recommendations for managing glyphosate-resistant Palmer amaranth. Additionally, comparisons will be made between Palmer amaranth and waterhemp and the potential for widespread glyphosate resistance in waterhemp in Iowa similar to that which has occurred in Palmer amaranth in the South. d d ra ft Abstract Herbicide resistance Herbicide resistance is defined by the Weed Science Society of America (WSSA 1998) as “the inherited ability of a plant to survive and reproduce following exposure to a dose of herbicide normally lethal to the wild type.” In the late 1990s, repeated use of the acetolactate synthase (ALS)-inhibiting herbicides (Scepter, Pursuit, Classic, Envoke, etc.) led to widespread resistance in Palmer amaranth, most recently resulting in removal of Palmer amaranth from several herbicide labels. Use of glyphosate-resistant technology In 1996, glyphosate-resistant soybean became commercially available followed by cotton in 1997 and corn in 1998. This technology was rapidly adopted in the southern U.S. partially because of its effectiveness on ALS-resistant Palmer amaranth and because of its ease of use. This technology was also adopted by Midwestern producers, but at a slower rate than in the South. Nationally in ra Collectively, there are approximately 6 million acres of agronomic crops in Arkansas compared with 23 million acres in Iowa. However, the evolution of glyphosate resistance has occurred at a more rapid rate in Arkansas and other southern states. Currently, there are five weeds in Arkansas that have evolved resistance to glyphosate, whereas only one in Iowa (waterhemp) is known to be resistant (Mike Owen, personal communication). Glyphosate-resistant Palmer amaranth d Glyphosate-resistant Palmer amaranth was first confirmed in Macon County, GA, in 2004 (Culpepper et al. 2006). The following year, glyphosate failed to control Palmer amaranth at sites in North Carolina, Tennessee, and Arkansas, with plants from these fields later confirmed resistant to glyphosate (Heap 2008). Glyphosate-resistant Palmer amaranth was found in South Carolina in 2006 and Mississippi in 2007. In each of these states, resistance rapidly went from being a perceived isolated occurrence to widespread infestations that were non-responsive to field rates of glyphosate. By 2008, resistance had been confirmed in more than 60 counties across six states, and most monitoring efforts have been discontinued because of widespread resistance. In Arkansas, two distinct glyphosate-resistant Palmer amaranth biotypes exist. Biotype I has a high level for resistance, resistant plants occur at high densities, and these plants rapidly colonize a field in a couple of years. Often, the infested areas cannot be harvested; hence, these fields are often mowed, tilled, or completely abandoned. Resistant plants in these fields are not controlled with glyphosate in excess of nine times the normal use rate. Biotype II is more typical in Arkansas than Biotype I and has a low level of resistance and possibly a different resistance mechanism. Buildup of resistant plants in a field is generally slower and more spatially dispersed than Biotype I plants and resistance is not noticeable until after 3 or 4 years. Multiple glyphosate applications at the normal use rate will not control the resistant plants; however, these plants are somewhat responsive to glyphosate in that the upper portion of the plant is often killed, leading to regrowth from lower axillary buds. Management changes To date, it is estimated that weed management practices have changed on 2 million acres as a result of glyphosate-resistant Palmer amaranth (personal communication with weed specialists throughout the South). Weed management programs that have been built solely around glyphosate are having to be restructured, meaning increases in operational costs. Glyphosate-resistant Palmer amaranth has definitely increased the complexity and costs of weed management. In addition, harvest efficiency, reduced yields, and in the most severe cases, complete crop loss and field abandonment have resulted. The ease of weed management decision-making brought forth by glyphosate-resistant crops is no longer a stand-alone option for many producers. A question that producers are having to answer is whether the point has been reached when convenience has become less efficient and can no longer be substituted for accuracy, consistency, and effective control? This is a challenging question to answer considering that farm size continues to increase as farm labor continues to decline. ft ft Soybean, rice, and cotton are the three largest acreage crops in Arkansas, with each grown on 2.8, 1.3, and 0.9 million acres, respectively, in 2007. Of this acreage, 98% of the cotton, 99% of the soybean, and 75% of the corn were glyphosate resistant in 2008. Comparatively, corn and soybean are the two major crops in Iowa with each grown on 13.9 million and 9.2 million acres in 2007. Although it may be perceived that crop rotation in Arkansas is equal to or greater than in Iowa, that is not the case. In addition to cotton not being rotated, rice is often grown in a 2:1 year rotation with soybean, leaving most of the remaining soybean acreage without a rotational crop. 2008 Integrated Crop Management Conference - Iowa State University — 171 It is well documented that the glyphosate-resistant technology reduced use of tillage. However, it is possible that conservation tillage will be compromised as part of the management solution. Finally, with glyphosate and the ALS-inhibiting herbicides now being ineffective on many Palmer amaranth populations, it is almost inevitable that resistance will evolve to other broadleaf herbicides, especially if steps are not quickly taken by weed scientists and producers to delay further resistance. Use of additional modes of action alone is not the answer. Recent modeling efforts with Palmer amaranth have shown that use of three modes of action in addition to glyphosate can lead to increases in resistance unless the weed is effectively controlled during the portion of the season when emergence is most probable. Furthermore, there are waterhemp populations in the Midwest that have evolved resistance to glyphosate, ALS-, and protoporphyrinogen oxidase-inhibiting herbicides (Reflex, Flexstar, Blazer, Valor, etc.) (Legleiter and Bradley 2008). Additionally, there are populations of Palmer amaranth and waterhemp that are resistant to photosystem II-inhibiting herbicides (AAtrex) (Heap 2008). ra 2006, 43% of the corn, 92% of the soybean, and 85% of the cotton in the U.S. were glyphosate resistant. Glyphosate-resistant traits in cotton were adopted to an even greater extent in the MidSouth and Southeastern U.S. In 2007, Arkansas, Louisiana, Mississippi, Missouri, Tennessee, Alabama, Florida, Georgia, South Carolina, North Carolina, and Virginia used glyphosateresistant technology on 97% or more of their cotton acreage. Cotton production in the U.S. is generally a monoculture system with crop rotation rarely practiced. Hence, glyphosate has been the main herbicide for weed control in cotton for the past 8 to 10 years. As modes of action are quickly lost, what is left? For certain, discovery, development, and use of new chemistries are not short-term solutions. As a result of broad-scale adoption of glyphosateresistant crops and almost sole use of glyphosate in these crops, many chemical companies merged in the late 1990s and herbicide discovery within most companies was discontinued until recently. Hence, there are no new herbicides that will be available in the near future. At best, if a herbicide was discovered today, assuming that it is highly effective for control of various Amaranthus species (pigweeds), it would be at least 7 years before the herbicide would be commercially available. d 170 — 2008 Integrated Crop Management Conference - Iowa State University In the short term as resistance spreads, producers have no option but to integrate additional modes of action into their weed management programs. There is a tremendous effort underway to better understand when in the cropping season to use alternate herbicides to achieve effective control while preserving modes of action from further resistance. Other strategies that are being investigated include use of cover crops to aid early-season weed suppression, possible crop rotations, precision cultivation, seed burial through deep tillage, and use of other herbicide-resistant traits. In 2009, glufosinate-resistant soybean (Liberty Link) will be available to producers on a limited basis. This may seem to be an effective option for Palmer amaranth control; however, glufosinate applications must be more timely than current glyphosate applications. Additional herbicide-stacked trait technologies are being developed for various 172 — 2008 Integrated Crop Management Conference - Iowa State University crops, but it is not likely that any of these technologies will become commercially available in the next 4 to 5 years. Is resistance restricted to the south? 2008 Integrated Crop Management Conference - Iowa State University — 173 References Culpepper, A. S., T. L. Grey, W. K. Vencill, J. M. Kichler, T. M. Webster, S. M. Brown, A. C. York, J. W. Davis, and W. W. Hanna. 2006. Glyphosate-resistant Palmer amaranth (Amaranthus palmeri) confirmed in Georgia. Weed Sci. 54:620-626. Franssen, A. S., D. Z. Skinner, K. Al-Khatib, and M. J. Horak. 2001. Interspecific hybridization and gene flow of ALS resistance in Amaranthus species. Weed Sci. 49:598-606. Palmer amaranth is not known to exist in Iowa. So, is glyphosate-resistant Palmer amaranth a threat to Iowa crops? Most certainly yes! Palmer amaranth and waterhemp coexist in fields in the central U.S. (Missouri, Illinois, Tennessee, etc.). Both species readily hybridize with each other as well as with other pigweeds (Franssen et al. 2001; Wetzel et al. 1999). It is known that gene flow in glyphosate-resistant Palmer amaranth can occur at appreciable distances via pollen (Sosnoskie et al. 2007), and based on the occurrence of glyphosate-resistant Palmer amaranth on well over 1 million acres throughout the South, it is likely that gene flow is occurring along with creation of genetically distinct populations. Additionally, recent evidence of seed movement leads to concern for establishment of new glyphosate-resistant Palmer amaranth populations in more northern environments. Wetzel, D. K., M. J. Horak, D. Z. Skinner, and P. A. Kulakow. 1999. Transferal of herbicide resistance traits from Amaranthus palmeri to Amarathus rudis. Weed Sci. 47:538-543. d Obviously glyphosate-resistant Palmer amaranth has had a devastating impact on crops in the southern U.S. and waterhemp could have a similar impact on Midwestern crops based on similarities between the two species. It is likely that extensive glyphosate resistance in waterhemp is a few years behind that of glyphosate resistance in Palmer amaranth for several reasons. First, the growing season in the Midwest is shorter; thus, there are fewer glyphosate applications and less exposure of waterhemp to glyphosate. Secondly, a corn/soybean rotation is widely used in the Midwest whereas there is more monoculture production of crops in the South. Additionally, both soybean and corn are more competitive than southern crops such as cotton; hence, corn and soybean more effectively shade late-emerging weeds and reduce to a greater extent seed production of weed escapes. Finally, adoption of glyphosate-resistant technology occurred more rapidly in the South, which has contributed to glyphosate resistance evolving earlier in this region. Dr. Larry Steckel at the University of Tennessee recently commented, “Glyphosate-resistant Palmer amaranth is a bigger threat to Mid-south agriculture than soybean rust will ever be.” Millions of dollars have been spent by the USDA and commodity boards on soybean rust research. It is my belief, similar to that of Dr. Steckel regarding glyphosate-resistant Palmer amaranth, that glyphosate-resistant waterhemp will have far more impact on Iowa’s soybean crop than rust will. A train wreck is coming. The question is can we prevent the wreck from happening? Legleiter, T. R. and K. W. Bradley. 2008. Glyphosate and multiple herbicide resistance in common waterhemp (Amaranthus rudis) populations from Missouri. Weed Sci. 56:582-587. ft Sosnoskie, L. M., T. M. Webster, J. M. Kichler, A. W. MacRae, and A. S. Culpepper. 2007. An estimation of pollen flight time and dispersal distance for glyphosate-resistant Palmer amaranth (Amaranthus palmeri S. Wats.). Proc. South. Weed Sci. Soc. 60:229. WSSA. 1998. Resistance and tolerance definitions. Weed Technol. 12:789. ra Final thoughts Heap, I. 2008. International Survey of Herbicide Resistant Weeds. Available at: http://www.weedscience.org/In.asp Accessed: Oct. 30, 2008. d ra ft Palmer amaranth and waterhemp have many similarities. Both are dioecious, producing either male or female plants, thus obligate outcrossers. Both exhibit a high amount of genetic diversity as a result of outcrossing, which has likely contributed to both weeds being highly prone to evolution of herbicide resistance. Susceptible biotypes of both weeds are highly sensitive to glyphosate; hence, there is tremendous selection pressure for resistant alleles. Both weeds are capable of producing in excess of 500,000 seeds/female plant, leading to a higher likelihood for resistance compared to species with lower fecundity. Palmer amaranth and waterhemp can exceed growth rates in excess of 2 inches in height/day making them two of the most competitive weeds of crops in the South and Midwest, respectively. Hence, they are able to proliferate in the presence of a less competitive crop. 174 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 175 Is there a need for stewardship or is killing weeds good enough? Micheal D. K. Owen, Professor, Agronomy, Iowa State University ra ft Since the introduction of glyphosate resistant (GR) soybean cultivars in 1996, GR crops have become the most rapidly and globally accepted agronomic practice in the history of agriculture(Anonymous 2007; Service 2007). In the United States (US), more than one billion cumulative acres of genetically engineered (GE) crops have been planted with most of these represented by GR crops (Gianessi 2005; Anonymous 2007; Service 2007; Gianessi 2008). Monsanto reported that their 2006 market share of glyphosate resistant crops (GRC) included 71.6 million acres of the soybean area, 34 million acres of corn, 11.3 million acres of cotton, and 5.7 million acres of canola in the US and Canada (Anonymous 2006b). They anticipate that their GRC market share in US corn will approach 60 million acres by 2010 (Anonymous 2006a). In Iowa, GR soybeans are planted on an estimated 97% of the acres and GR corn is approaching 75% of the acres. All of the GR crops likely receive at least one and more often, two or more applications of glyphosate for weed control. Growers like the perception of simplicity and convenience of the GR-based crop systems, the consistent control of weeds and the lack of crop injury from glyphosate. However, despite the appearance of a successful weed control program, the soybean producer often fails to recognize the cost of simplicity and convenience: given the widespread adoption of GR crop systems, weed populations are changing and there is a critical need to include glyphosate stewardship in GR crop systems. The concurrent use of glyphosate in GRCs has resulted in the evolution of weeds that are resistant to glyphosate (Figure 1). There are now 14 different weed species that have glyphosate resistant biotypes (Heap 2004). Nine glyphosate resistant weed species have been identified in the US and six were confirmed glyphosate resistant since 2004. Importantly, it is apparent that weed populations are evolving resistance to glyphosate at an increasing rate. While alternative herbicides may still be effective and provide control of the glyphosate resistant weeds, resistance to many of the alternative herbicides also exists. Currently 183 herbicide resistant weed species are identified and many of these weeds are found in Iowa (Heap 2004). Thus it is critical to understand the implications of current weed control practices on future weed problems and assess the need to implement stewardship proactively to protect the sustainability of GRCs. d d ra ft Introduction What are the implications of current weed control tactics? The observed and anticipated problems that are evolving in GR crop systems are a product of the success of the system. Importantly, growers seem unwilling to change what they incorrectly perceive to be a successful weed control system. Many of the problems and issues associated with the GR crop systems are not easily seen or measured. Recognize that weeds behave differently than other pest complexes; their impact on crops (i.e. lost yield potential) is typically subtle and the evolution of new weed problems (i.e. evolved glyphosate resistance) occurs over a number of years. However given the seed production demonstrated by weeds and dormancy in the seeds, once the weed becomes established in a field, the problem will remain for an ft Throughout the US, weed communities in GR-based crop systems are responding to the recurrent use of glyphosate and weed populations are adapting to the management practices. Furthermore, given the adoption of the GR-based crop systems, particularly in soybean and cotton, there has been a significant decline in the use of “alternative” herbicides (Shaner 2000; Young 2006). The lack of herbicide diversity and the consistent use of glyphosate have created an ecological environment where changes in weed communities are inevitable. d ra In order to assess these changes in weed communities, surveys were administered to growers and AgChem professionals from Iowa. The surveys addressed, in a general sense, the ecological implications of current weed control practices and indicated that a number of Iowa growers and AgChem dealers believe that fields are becoming weedier and weeds now require higher rates or more frequent applications of glyphosate for effective control (Tables 1 and 2). Interestingly, AgChem professionals consistently reported a higher concern than growers. There is no question that glyphosate has provided excellent and consistent weed control in most fields. Furthermore, most of the problems reported are likely attributable to poor management strategies (i.e. low glyphosate rate or application to large weeds). However, it is concerning that 40% of the AgChem professionals reported that fields were becoming weedier since the adoption of GR crops (Table 1). While only 26% of Iowa growers surveyed reported that fields were becoming weedier, this percentage is still high and suggests that there is a critical mass of issues developing across the state (Table 1). More telling was that growers were almost equally split as to whether more glyphosate was needed to achieve effective weed control (45% indicating more glyphosate versus 49% indicating their current use practice was still effective) (Table 2). A much higher percentage of AgChem professionals felt that fields were becoming weedier (40%) and more glyphosate was needed for effective control (57%) (Tables 1 and 2). Given that growers tend not to “see” a potential problem until it evolves in their fields, and that AgChem professionals likely have the “bigger picture”, the reported differences between the groups are not surprising. Regardless, both responding groups suggested that the situation with GR crops and glyphosate were changing and not in a positive direction. When these same questions were posed about specific weeds, similar trends between growers and AgChem professionals were observed with one notable exception (Tables 3 and 4). Growers and AgChem professionals were in agreement that common waterhemp problems were increasing and more glyphosate was required for effective control. AgChem professionals reported that common lambsquarters and giant ragweed problems were increasing, 62% and 55%, respectively and that more glyphosate was needed for effective control, 56% and 50%, respectively (Table 3). Only 37% of growers reported that common lambsquarters problems were increasing and 56% reported that control with glyphosate had not declined (Table 4). Similar responses for giant ragweed were reported (Table 4.) AgChem professionals and growers were in agreement that neither Asiatic dayflower or common ragweed were increasing problems and these weeds continued to be effectively controlled with current glyphosate usage practices (Tables 3 and 4). It is noteworthy that the three weeds, common lambsquarters, common waterhemp and giant ragweed, most frequently are identified as increasing problems and responding less to current glyphosate usage practices have been identified as having evolved glyphosate resistant populations (Heap 2004). These changes in weed populations are an inevitable consequence of the consistent and widespread use of simple and convenient weed management programs such as those employed by growers when they plant GR crops and apply glyphosate. The selection pressure imposed by consistent use of glyphosate without additional control tactics will result in weeds that no longer to those simple and convenient tactics (Christoffoleti et al. 2008). Economic implications of current weed control tactics; reduced crop yield potential ft Changes in weeds attributable to current weed control tactics; ecological responses to the system 2008 Integrated Crop Management Conference - Iowa State University — 177 The important issue in current glyphosate use tactics and the lack of stewardship practices is economic. Convenience and simplicity, as the current weed control tactics are deemed, have significant costs and growers must understand these costs in order to make the best objective decision about how to best use the GR crop technology and glyphosate. Economics should play the most important role on glyphosate stewardship. From the perspective of the author, if an objective assessment of the GR crop system is done, there is a strong and pervasive economic argument to implement stewardship for glyphosate. Unfortunately, this requires that weed control tactics assume a greater management posture (i.e. planning and timeliness) which will be less simple and perceived as inconvenient by growers and some AgChem professionals. Growers tend not to do anything to proactively address issues until the problems are experienced locally (Foresman and Glasgow 2008). Furthermore, many growers and AgChem professionals believe that new technologies, either new herbicide or herbicide resistant traits, are eminent and will resolve the current emerging problems with glyphosate. These technologies are not likely to be available for a number of years and by themselves, have limited abilities to fix that which is becoming broken in GR crop systems given the lack of stewardship toward glyphosate (Sammons et al. 2007). ra extremely long time. By the time growers recognize that there is a new weed problem, it is too late. The primary issues associated with the current weed control tactics in GR crops are ecological problems and economic losses. d 176 — 2008 Integrated Crop Management Conference - Iowa State University Glyphosate can control most weeds irrespective of size and thus growers tend to favor total postemergence programs. However, given the predominance of GR crops and the use of postemergence applications of glyphosate, the ability to make timely and accurate applications is severely compromised. Unfortunately, many glyphosate applications are delayed beyond a timing that is best for the protection of crop yields. A significant part of the problem is that it is difficult to “see” the impact of weeds on potential yield, particularly when there is no comparison available. Typically, growers and AgChem professionals see dead weeds in the fields and presume that they have implemented a successful weed management program. However, the reality is that delayed or reduced rates of glyphosate will result in a situation where weeds compete for potential crop yield even though the weeds may ultimately be controlled. Average weed infestations compete early and effectively for crop yield; a one day delayed application of glyphosate may cost more than a preemergence residual herbicide, depending on crop price and yield potential (Hartzler, personal communication). Delayed weed control of five to ten days may result in potential soybean losses of two to six bushels per acre, again depending ra ft When weed problems evolve in GR crops, it is likely that there is a lack of diversity in the weed management program. Importantly, the benefits of glyphosate stewardship will be realized first in improved profitability by eliminating early weed competition resulting in higher crop yields. Longer term benefits of glyphosate stewardship include the delay or elimination of evolved resistance to glyphosate in weed populations. It is important to always use a soilapplied residual herbicide either early preplant or preemergence to the crop. Not only does this provide protection to potential crop yield, but it diversifies the weed management program and, importantly, provides an opportunity for better time management later in the growing season. The best choice is an herbicide that has activity on the earliest germinating weeds and those that are most problematic in the field. It is also wise to target the choice of herbicide for weed species that have demonstrated the ability to evolve resistant populations to glyphosate (i.e. common waterhemp). By using a residual herbicide in GR crops prior to postemergence glyphosate application, potential crop yields are protected, selection pressure from glyphosate is reduced, and there is a longer period of time before weeds begin to compete with crop yields. d Another issue is the guaranteed respray programs. Resprays are potentially costly from the perspective that they may not occur in a timely fashion and thus potential crop yield is lost. Also important is the “free” resprays increase selection pressure on the weeds increasing the possibility of evolved resistance to glyphosate. Thus, it is important to diversify the weed management program as much as possible, whether with other herbicides or alternative tactics. Use herbicides with different modes of action but recognize simply using a different herbicide will not improve glyphosate stewardship if the herbicide of choice does not have activity on the target. While crop rotation should generally be considered an effective steward tactic, rotating GR soybeans with GR corn is not a good tactic for glyphosate stewardship unless herbicides other than glyphosate or alternative tactics are used for weed management. Avoid repeated applications of glyphosate. Avoid delaying glyphosate applications in order to be more “efficient”; delaying an herbicide application to accommodate a second pesticide likely costs crop yield potential from both pest complexes. Simple stewardship tactics can provide considerable benefit and protect the GR crop trail and glyphosate. For example, scout fields and observe and manage weed problems when they are just beginning. Keeping records for each field will provide valuable information about the risks of choosing a weed management program for the future. Develop individual weed management programs that address the problems and conditions unique to that field. While this practice is neither simple nor convenient, it will provide long term stewardship and increase profitability. Summary The biggest problem with implementing glyphosate stewardship is that the growers and AgChem professionals are not convinced that a weed problem exists until it is discovered on locally. Given weed seed productivity and dormancy, once a problem is discovered, it is too late to “fix”. In essence, glyphosate stewardship plans should be implemented before a problem with glyphosate exists. Another issue is that growers are concerned that using residual herbicides will add needless cost to crop production. Importantly, weeds are ubiquitous but yield losses are often overlooked because there is not opportunity to measure difference attributable to different tactics. Ultimately all acres are treated with herbicides. It is critical to recognize that just because the weeds are killed does not mean the weed control program has been successful. Furthermore, the consistent use of glyphosate will ultimately result in problems that cannot be easily managed; these shifts in weed populations will occur sooner rather than later. Thus, it is critically important to implement a glyphosate stewardship program now. Use an appropriate residual herbicide on all crop acres and follow with post-applied glyphosate as needed. Table 1. Fields are becoming more “weedy” Sample population Iowa growers (n=6588) Iowa AgChem professionals (n=568) ft What are the best tactics for the stewardship of glyphosate? 2008 Integrated Crop Management Conference - Iowa State University — 179 Yes No 26% 70% 40% 57% Table 2. More glyphosate is needed (application frequency or rate) ra on the anticipated yield and weed infestation. Importantly, glyphosate resistant weeds obviously will be poorly controlled are guaranteed to compete with crop yield potential. It is critical to remember that herbicides are used not to control weeds but rather protect crop yield potential. Sample population Yes No Iowa growers (n=6588) 45% 49% Iowa AgChem professionals (n=568) 57% 39% d 178 — 2008 Integrated Crop Management Conference - Iowa State University 180 — 2008 Integrated Crop Management Conference - Iowa State University Table 3. Survey conducted in 2007 to assess the attitudes of Iowa AgChem professionals on glyphosate and weed problems (568 respondents) 2008 Integrated Crop Management Conference - Iowa State University — 181 16 14 % responses: weed problem increasing % responses: control with glyphosate declined Yes 62% 56% No 37% 39% Yes 61% 53% No 36% 42% 8% N/A 81% N/A 55% 50% 40% 46% Figure 1. Evolved weed resistance to glyphosate since the introduction of glyphosate resistant soybeans. Yes 29% 29% Anonymous. (2006a). Fourth-quarter 2006 financial results (Monsanto). No 68% 64% Anonymous. (2006b). Monsanto biotechnology trait acreage: fiscal years 1996 to 2006. Yes No Giant ragweed No ra Yes Common ragweed Table 4. Survey conducted in 2008 to assess the attitudes of Iowa growers on glyphosate and weed problems (6588 respondents) % responses: weed problem increasing % responses: control with glyphosate declined Yes 37% 34% No 55% 56% Yes 51% 42% No 43% 49% Weed d Common lambsquarters Common waterhemp Asiatic dayflower Yes 5% N/A No 77% N/A W e e d s 10 8 6 4 2 0 ft Asiatic dayflower ft Common waterhemp # 12 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Year ra Common lambsquarters Anonymous. (2007). ISAAA Brief 37-2007: Executive Summary Global status of commercialized biotech/GM crops: 2007 (International Service for the Acquistion of Agri-Biotech Applications), pp. 12. Christoffoleti, P. J., A. J. B. Galli, S. J. P. Carvalho, M. S. Moreira, M. Nicolai, L. L. Foloni, B. A. B. Martins, and D. N. Ribeiro. 2008. Glyphosate sustainability in South American cropping systems. Pest Management Science 64:422-427. Foresman, C., and L. Glasgow. 2008. US grower perceptions and experiences with glyphosateresistant weeds. Pest Management Science 64:388-391. d Weed Gianessi, L. P. 2005. Economic and herbicide use impacts of glyphosate-resistant crops. Pest Management Science 61:241-245. Gianessi, L. P. 2008. Economic impacts of glyphosate-resistant crops. Pest Management Science 64:346-352. Heap, I. (2004). The international survey of herbicide resistant weeds. Yes 35% 35% Sammons, R. D., D. C. Heering, N. Dinicola, H. Glick, and G. A. Elmore. 2007. Sustainability and stewardship of glyphosate and glyphosate-resistant crops. Weed Technology 21:347-354. No 60% 55% Service, R. F. 2007. Glyphosate - the conservationist’s friend? Science 316:1116-1117. Yes 26% 25% No 63% 63% Shaner, D. L. 2000. The impact of glyphosate-tolerant crops on the use of other herbicides and on resistance management. Pest Management Science 56:320-326. Giant ragweed Common ragweed Young, B. G. 2006. Changes in herbicide use patterns and production practices resulting from 182 — 2008 Integrated Crop Management Conference - Iowa State University glyphosate-resistant crops. Weed Technology 20:301-307. 2008 Integrated Crop Management Conference - Iowa State University — 183 Update in weed management 2009 – has the silver bullet been developed? Micheal D. K. Owen, Professor, Agronomy, Iowa State University ra ft The short answer to the question posed in the title of this paper is an unqualified and emphatic no! While there are new technologies, herbicides and formulations available, they represent only additional tools that will be helpful in implementing a successful weed management program. An emphasis must be placed on the “helpful” and “management”, neither of which meets grower desires for simple, convenient, and cheap weed control tactics. While the glyphosate based systems are generally successful (still) in killing weeds (see “Is there a reason to consider stewardship or is killing weeds good enough?” which appears in this proceedings), there is no longer a question as to whether or not the system is beginning to weaken and problems are exhibiting themselves. In fact, more complaints concerning the performance of glyphosate on a number of weeds are received at an increasing rate. Thus, it is critically important to review the tools that are available and design the most effective and diversified weed management program possible. While this effort will require more thought and consideration than growers and AgChem professionals have become accustomed, it will pay dividends in the long term, both with regard to minimizing changes in the weed community and improving profitability. Silver bullets for weed management have never existed. This paper will describe a number of new technologies from a number of companies; not all companies or all technologies will be covered. The inclusion of a technology should not be construed as an endorsement or the exclusion suggests that the technology is not acceptable. Aceto Agricultural Chemicals Corp Halomax 75 will be registered for postemergence application in corn. Halomax 75 is similar to Permit 75WG, formulated as a WDG (wetable dry granule) and contains 75% halosulfuron as the active ingredient. Halomax 75 control yellow nutsedge and has activity on common ragweed, giant ragweed, pigweed species, and velvetleaf. However, Halomax 75 is an ALS inhibitor herbicide and does not effectively control ALS resistant weed biotypes. d d ra ft Introduction AMVAC AMVAC has a supplemental label for Impact® herbicide in field corn, popcorn and sweet corn. The supplemental label allows a maximum application of 1.0 fluid ounce per acre, either as a single or sequential treatment. Do not apply Impact within 45 days of corn harvest or graze or feed treated corn forage, silage, fodder or grain within 45 days after application. With the 1.0 fluid ounce rate, there are rotational restrictions of nine months for alfalfa and sorghum, and an 18 month rotational restriction for soybeans in Iowa. Soybean rotation intervals for 0.5 and 0.75 fluid ounces per acre remain unchanged. Impact® is registered for aerial application and is not restricted to stage of corn development (refer to harvest and feeding restrictions listed above). There was interest in applying Impact® by aircraft during the 2008 growing season due to adverse conditions that precluded ground applications. ft BASF Crop Protection is developing a new herbicide technology they have named KixorTM. While not currently registered, the registration dossier has been submitted and registration is expected during the third quarter 2009. Kixor™ is described as a highly effective herbicide with contact and residual activity preemergence in a number of cropping systems. This product demonstrates activity on a number of broadleaf weeds including those that have evolved resistance to glyphosate, ALS and triazine herbicides. Thus far, the new technology has demonstrated favorable environmental, toxicological, and ecotoxicological profiles. A number of formulations are anticipated. ra Distinct® is now registered as a burndown herbicide for soybeans. Apply two to four ounces per acres to control emerged broadleaf weeds at least 30 days prior to soybean planting. Another restriction describes the need for a minimum of one inch of rainfall or overhead irrigation prior to soybean planting. Other changes in BASF Crop Protection include the registration of Status® on popcorn (apply five to ten ounces per acre when popcorn is four to 36 inches tall at least 15 days prior to tassel emergence), Prowl H20 on asparagus and several brassica crops, and the discontinuation of Marksman® and Celebrity Plus®. Bayer CropScience d Balance Flexx® is a new formulation of isoxaflutole (previously marketed as Balance Pro®) for corn that includes the proprietary safener Cyprosulfamide (Crop Safety Innovation (CSI) SafenerTM). The safener enhances the metabolism of the isoxaflutole in the crop while maintaining highly effective weed control. Balance Flexx® will be registered for preplant (surface or incorporated), preemergence and postemergence application (up to the V2 stage of corn) and will provide excellent activity on a number of weeds including weeds that have evolved resistance to ALS, triazine and glyphosate herbicides. A number of tankmix combinations are described on the label which is anticipated early in 2009. Another new “product” that is currently under EPA review is CorvusTM Herbicide. While not currently registered, it is anticipated that this prepackage mixture of isoxaflutole plus thiencarbazone-methyl and their proprietary crop safener (CSI) cyprosulfamide will be available in 2009. Isoxaflutole is an HPPD inhibitor herbicide while thiencarbazone-methyl is an ALS inhibitor herbicide. The CorvusTM Herbicide formulation will be a suspension concentrate which includes 0.75 pounds active ingredient thiencarbazone-methyl and 1.88 pounds active ingredient isoxaflutole for a total of 2.63 pounds active ingredients of herbicide per gallon of formulated product. The formulated product also includes 1.25 pounds per gallon cyprosulfamide. CorvusTM Herbicide will be registered for field corn and popcorn and sweet corn will not be included on the anticipated label. The label has cautionary statements that suggest corn hybrids and certain male pollinators within blended corn varieties vary in their sensitivity to CorvusTM Herbicide. Replanting restrictions specify that only field corn can be replanted within the growing season after CorvusTM Herbicide application. It is anticipated that CorvusTM Herbicide will be registered for post-harvest applications in the fall or early spring, preplant surface-applied, preplant incorporated, preplant/preemergence burndown, preemergence and early postemergence applications. Restrictions for the use of organophosphate and carbamate insecticides will be included in the label. No aerial application is allowed. Control of a number of economically important annual grasses, broadleaf and winter annual weeds will be described on the anticipated label. Ignite® 280 SL Herbicide will replace Liberty® for use in Liberty Link® corn and soybean cultivars and can also be used in conventional and transgenic varieties of corn and soybeans as a broadcast burndown prior to planting or emergence of the crop. Ignite® 280 SL Herbicide should be applied from emergence of Liberty Link® corn through the fifth leaf (V5) at 22 ounces per acre. Do not apply more than 44 ounces per acre of Ignite® 280 SL Herbicide on corn per growing season. In Liberty Link® soybeans, applications can be made from emergence up to but not including bloom. For both crops, do not apply more than two applications per season and sequential applications should be at least 10-14 days apart. Ignite® 280 SL Herbicide applied at 22 ounces per acre is the equivalent amount of 30.7 ounces of Liberty®. The addition of 3 pounds of ammonium sulfate per acre is required for Ignite® 280 SL Herbicide application to Liberty Link® corn. Refer to the Ignite® 280 SL Herbicide for other restrictions and application requirements. ft BASF 2008 Integrated Crop Management Conference - Iowa State University — 185 LaudisTM (tembotrione) was introduced for commercial use for weed control in corn in 2008 and demonstrated excellent weed control and crop safety. LaudisTM is an HPPD inhibitor herbicide (bleacher) with relatively high specific activity on sensitive plant species. As such, the movement of LaudisTM to non-target areas was readily observed in 2008. Injury in soybeans in isolated situations was relatively widespread in fields to the extent that the potential for the volatilization of LaudisTM was questioned. The evidence is good that the formulation of tembotrione does not volatilize; data suggests that other HPPD inhibitor herbicide have a higher vapor pressure than LaudisTM but are not subject to concerns for volatilization. As a comparison, LaudisTM has a vapor pressure five to six-fold (100,000 to 1,000,000 X) less than dicamba (Banvel® formulation). However, these physicochemical properties do not fully explain the injury to soybeans that was observed in isolated instances in 2008. ra However, aerial application is not advisable given the mechanism of action (inhibition of plant pigments – “bleaching”), the relative sensitivity of non-target plants (i.e. soybeans), and the high drift potential from aerial applications. When the potential for drift is considered, aside from the environmental conditions that occurred during application, the other factor that must be considered is the relative sensitivity of the nontarget plant species. Anecdotal evidence suggests that soybeans are more sensitive to LaudisTM than either Impact® or Callisto®. Thus it requires less LaudisTM to drift and cause significant symptoms in soybeans. Importantly, LaudisTM is no more prone to drift than any other herbicide. However, while the actual amount of tembotrione moving was quite low, the result was obvious symptoms of HPPD herbicide injury. The point is that an extremely low amount of LaudisTM might move a longer distance (thus suggesting volatilization) and cause injury to soybeans because of the high relative sensitivity of the soybeans to LaudisTM. However, the evidence is clear that LaudisTM does not volatilize, but small amounts that can drift a relatively long distance and can cause obvious injury to sensitive species. Thus the onus is on the applicator to make sure that drift does not occur and that spray tank contamination is eliminated. d 184 — 2008 Integrated Crop Management Conference - Iowa State University In 2009, Liberty Link® soybean varieties will be introduced for limited commercial use. Liberty Link® soybean varieties will allow the topical application of the non-selective, non-residual herbicide Ignite® 280 SL Herbicide and will provide an alternative strategy for the control of a broad spectrum of weeds, and ALS, triazine, and glyphosate resistant weeds, specifically. The use tactics for Ignite® 280 SL Herbicide have been described previously in this paper. It is important to 186 — 2008 Integrated Crop Management Conference - Iowa State University DuPont DuPont is developing a new postemergence herbicide with residual activity for non-crop markets, pasture and rangeland. The new herbicide will control a broad spectrum of broadleaf weeds and the label has been submitted with first registration anticipated in 2010. The new product is classified as a hormone mode of action. d New products for DuPont include Accent® Q and Steadfast® Q. These products are similar to Accent® and Steadfast® but include a safener. Federal labels have been approved and state labels are pending. Prequel® (rimsulfuron plus isoxaflutole) label has been submitted. There are no changes on the Canopy® EX, Canopy®, EnviveTM, EnliteTM, and Synchrony® XP labels for 2009. Resolve® Q is a multipack combination of thifensulfuron, rimsulfuron and a safener. It will be positioned as a tankmix partner with glyphosate in glyphosate resistant corn and will provide some residual control of sensitive weeds. However, given that Resolve® Q is a combination of ALS inhibitor herbicides, ALS resistant weeds that have also demonstrated resistance to glyphosate (i.e. common waterhemp) will not be controlled. Apply 1.25 ounces of Resolve® Q per acre in combination with glyphosate and 0.75 pounds atrazine per acre to glyphosate resistant corn up to 20 inches tall or up to and including six leaf collars, whichever is more restrictive. RequireTM Q is a multipack combination of rimsulfuron, dicamba and a safener, and will be positioned as a tankmix partner with glyphosate in glyphosate resistant corn. RequireTM Q will provide improved broadleaf weed control and some residual grass control. The dicamba in the multipack should help control ALS and glyphosate resistant weeds. The application of RequireTM Q should be delayed until corn reaches four inches in height or V2. Do not apply to corn that exhibits seven leaf collars or is taller than 20 inches, whichever is more restrictive. The introduction of Optimum® GAT® technology for soybeans has been delayed until 2011, FMC ft FMC has a number of label additions and new products for 2009. Authority® Assist (sulfentrazone and imazethapyr) will be positioned as a preemergence product in Roundup Ready® soybeans in an effort to supplement and steward glyphosate. Authority® Assist will provide some residual control of small seeded annual broadleaf weeds and grasses. Applications can be made early preplant (up to 45 days prior to planting) and preemergence until three days after planting. Early preplant applications should use the highest label rate for the soil texture and organic matter. CadetTM Herbicide is a new product for FMC, however the active ingredient fluthiacet-methyl was developed by KI America and Novartis (now Syngenta) in the mid-1990s as Action® but was never commercialized. CadetTM Herbicide is registered for corn (including field corn, sweet corn, and popcorn) and soybeans as a tankmix partner for glyphosate for improved control of broadleaf weeds. CadetTM Herbicide is particularly strong on velvetleaf but also has activity on common waterhemp and common lambsquarters. Use 0.4 to 0.9 fluid ounces per acre; the 0.4 ounces per acre rate is recommended for a combination with glyphosate. Applications must be made after emergence of the crop and weeds. In soybean, apply CadetTM Herbicide from the first trifoliate until full flowering stage. In corn, apply CadetTM Herbicide from the two leaf stage (two visible leaf collars) until the corn is 48 inches tall or prior to tasseling, whichever comes first. ra ra ft However, it must be recognized that the objective of herbicide use is not to control weeds but rather to protect potential crop yield. Thus strictly from the economic perspective, application timing for Ignite® 280 SL Herbicide and glyphosate are similar; these herbicides should be applied earlier than later in order to most effectively protect potential crop yield as well as consistently control a broad spectrum of weeds. With regard to helping manage herbicide resistant weeds, Ignite® 280 SL Herbicide provides another excellent tool and will help manage ALS, triazine and glyphosate resistant weed populations as long as glufosinate has activity on the target weed species. However, the recurrent use of Ignite® 280 SL Herbicide will impose selection pressure on the weed community ultimately resulting in weed populations that are not effectively controlled by glufosinate, whether the result of evolved resistance or shifts to naturally tolerant species. Stewardship of Liberty Link® and Ignite® 280 SL Herbicide must be an immediate consideration when these technologies are adopted by growers. 2008 Integrated Crop Management Conference - Iowa State University — 187 pending US regulatory approvals and field testing. The delayed introduction of Optimum® GAT® soybeans is due to an effort by DuPont and Pioneer to utilize more effective technologies available and introduce the traits into new elite germplasm. Optimum® GAT® technology for corn continues on schedule with an anticipated commercialization of 2010. RageTM D-Tech Herbicide is a combination of carfentrazone-ethyl and the ethylhexyl ester of 2,4D and is registered as a burndown treatment in corn and soybean. Depending on the application rate, there is seven to 14 days planting interval in soybeans. In corn, again depending on the application rate, there is a three to 14 days planting interval. RageTM D-Tech Herbicide can also be applied in corn from spike to the five leaf stage (eight inches tall) as a broadcast application at eight fluid ounces per acre or with drop nozzles at 12 fluid ounces per acre to corn up to 14 leaf collars or 36 inches tall. Weeds should be four to six inches in height. d recognize the strengths and limitations of this alternative system for weed control. While Ignite® 280 SL Herbicide controls a great number of grass and broadleaf weeds in Liberty Link® soybean, the active herbicide ingredient in Ignite® 280 SL Herbicide does not translocate like glyphosate. Thus, application timing is more critical in order to control weeds when they are relatively small. Furthermore, the control of perennial weeds is not the strength of Ignite® 280 SL Herbicide compared to glyphosate. Gowan Gowan has a number of new products in their extensive generic herbicides portfolio. Those products that are of particular interest to Iowa include Imperium® (EPTC plus acetochlor), Permit® (halosulfuron-methyl), Targa® (quizalofop-P-Ethyl), Yukon® (halosulfuron-methyl and dicamba), TNT BroadleafTM Herbicide (thifensulfuron-methyl and tribenuron-methyl) and UnityTM WDG Herbicide (thifensulfuron-methyl). Imperium® is now registered for use on sweet corn. TNT BroadleafTM Herbicide and UnityTM WDG Herbicide are equivalent to Harmony® Extra and Harmony® GT herbicides, respectively. TNT BroadleafTM Herbicide is registered as a burndown treatment in corn and soybeans and application should be at least 14 days prior to planting. UnityTM WDG Herbicide can be used as a preplant burndown treatment and should be applied before crop emergence. 188 — 2008 Integrated Crop Management Conference - Iowa State University Monsanto ft MANA (Makhteshim Agan of North America, Inc.) has a number of generic herbicides available including Arrow® 2EC (clethodim), Glyphogan® (glyphosate), Parallel® , Parallel PCS®, and Parallel Plus®, (metolachlor) and Parazone® 3 SL (paraquat). ra Harness® and Degree® are no longer listed as restricted use herbicides and have new uses and additional rotational crops included on the label. Sweet corn will be added to these labels and rotational crops for the following growing season will include sugar beets, sunflowers, alfalfa, clover and others. It is anticipated that Harness Xtra® and Harness Xtra® 5.6L will be labeled for sweet corn in 2009, as well as have changes in rotational crops allowed. Monsanto continues to expand their efforts for stewardship of glyphosate and Roundup Ready® crops by adding additional alternative herbicides to the suggested uses described in the Technical Use Guide. Syngenta d Syngenta has a number of label revisions to consider. Princep Caliber 90 and Princep 4L are prohibited for aerial application and have revised drift management language. PrefixTM (prepackage mixture of s-metolachlor plus fomesafen) is registered for postemergence application in soybeans and can be applied at cracking through the third trifoliate. Injury to the soybean is likely but symptoms are temporary. PrefixTM application should be made at least 90 days prior to harvest. PrefixTM should not be applied postemergence to soybeans that have been treated with an s-metolachlor product. The Reflex® label has a number of changes. New wording about application timing, soybean injury, environmental conditions and weed resistance is included. Changes also exist in the section describing spray additives and replant options. Preplant surface and preemergence applications of Reflex® are included in the label and new tank mixture combinations are described. The Flexstar® label describes a tankmixture with glyphosate of up to 1.5 pint per acre to control glyphosate resistant weeds in Roundup Ready soybeans. Dual Magnum® is now registered for pumpkins, rhubarb and horseradish. Language describing the postemergence application of Dual Magnum® is included and states clearly that while this herbicide can be applied postemergence to crops (corn, soybeans, and others), but will not control emerged weeds unless a herbicide with postemergence activity to weeds is included. Corn can be treated with Dual Magnum® after emergence until 40 inches tall while soybeans can be treated from emergence through the third trifoliate. Callisto® is now registered for tankmixtures with Liberty® (glufosinate), Stout® (nicosulfuron plus thifensulfuron) and glyphosate postemergence in glyphosate resistant corn. Burcucumber is now included on the list of weeds “controlled” by Callisto®. The statement describing the aerial application restrictions with Callisto® has been revised (but does not allow aerial application) and a number of new crops have been added to the Callisto® label. United Phosphorus Inc. ft MANA UPI has a number of generic herbicides that are available for use in Iowa corn and soybean production. These include SamsonTM 4SC Herbicide (nicosulfuron), MetriTM Herbicides (metribuzin), Clopyr® AG Herbicide (clopyralid), Storm® Herbicide (bentazon and acifluorfen), and Ultra Blazer® Herbicide (acifluorfen). ra Loveland has introduced MakazeTM Herbicide (isopropylamine salt of glyphosate) with Leci-TechTM proprietary technology. MakazeTM Herbicide is formulated to provide superior droplet penetration, spreading, uptake and penetration according to the Loveland literature. MakazeTM Herbicide is labeled for use in Roundup Ready® corn and soybeans and has been evaluated by numerous land grant universities. 2008 Integrated Crop Management Conference - Iowa State University — 189 The Camix® label has added a use precaution that indicates other solo HPPD inhibitor postemergence herbicides (Callisto®, Impact® or Laudis®) should not be applied to ground previously treated with Camix® in the same season. Similar statements are included in the Lexar® and Lumax® labels. Camix®, Lexar®, and Lumax® labels have revised weed resistance management language and caution about repeat applications of HPPD inhibitor herbicides during the same growing season. These sections also advise that two or more herbicide modes of action should be included as a good weed resistance management strategy. These herbicide labels also include revisions in the rotational crops section. Valent Valent has registered Valor® SX for application on minimum and no tillage corn. Application of 1.0 to 2.0 ounces per acres must be made 14 to 30 days prior to planting. Valor® SX can also be applied in the fall but no earlier than October 15 or when soil temperature falls below 50° F at the two inch depth. This treatment will help control a number of winter and early spring annual weeds. Conclusions d Loveland Products, Inc. It is apparent that many companies continue to develop new and useful herbicides that offer important strengths for weed control in corn and soybean. It is also apparent that while these herbicides can be designated as “new” by a number of criteria, there has not been any new herbicides with new mechanisms of action. Importantly, the new products tend to have very specific usages and strengths and thus do not represent the newest “silver bullet” opportunity. Given the rapidly changing weed problems in Iowa, the best opportunity for growers is to apply appropriate Integrated Weed Management (IWM) and consider that unless a conscious and consistent stewardship effort is made, the ability to manage weeds will erode and profitability will quickly decline. While using IWM is not simple (and possibly convenient), neither is trying to develop a “quick fix” to resolve weed control problems after the fact. Recognize that when weed control problems evolve, they always cost more money than the appropriate well-thought tactic that should have been used in advance of the problem. Finally, when weed problems evolve, they will remain problems for a long time – develop IWM stewardship strategies and apply them before the weed problems occur. 190 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 191 Fertilizer costs and crop production in 2009 David Asbridge, Doan Advisory Services ft ICM Conference Ames, Iowa ra David Asbridge Doane Advisory Services December, 2008 1 d d ra ft Fertilizer Situation & Outlook Nit Nitrogen Situation & Outlook 2 192 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 193 World Nitrogen Demand U.S. Nitrogen Supply (MM Tons N) (MM Metric Tons) “Imports now account for roughly 45% of total U.S. nitrogen supply” 160 20.0 140 18.0 120 16.0 1990-2002 1.1% Growth 100 Imports 14.0 12.0 Domestic P d ti Production 6.0 4.0 2.0 0.0 98 99 00 01 02 03 04 05 06 07 60 NonFerts F tili Fertilizers ft 8.0 ft 80 10.0 40 20 0 08 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 Fertilizer Years Calendar Years World Nitrogen Price Index World Nitrogen Fertilizer Demand (Average 2003 = 100) Ammonia d 100 80 Long-Term Trend 350 150 50 J04 J05 J06 Rest of World 60 250 J03 “China and India now account for roughly 45% of world N fertilizer d 450 (MM Metric Tons) Recent Spike Urea 5 ra ra 3 550 2002-07 3.7% Growth J07 40 India 20 China 0 J08 January 2003 - Current 00 01 02 03 04 05 06 07 08 Calendar Years 4 6 194 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 195 Growth in World Nitrogen Fertilizer Demand Since 2000 (MM Metric Tons) U.S. Ammonia and Urea Capacity (Million Tons of Product) 25.0 8.0 7.0 Ammonia Urea 20 0 20.0 Ammonia A i Urea 6.0 5.0 % 2007 Change 2000 20.2 20 2 9.6 12.3 12 3 6.9 -39% 39% -28% 15.0 3.0 20 2.0 1.0 0.0 China India Rest of World 02 04 06 Calendar Years ra 9 1994 -2000 17.1 MM d 2004 - 2010 23.6 MM 5.0 5 0 d 120 4.0 100 3.0 80 2.0 Capacity Production 1.0 20 Calendar Years Source: Various 8 10 08 06 04 02 00 98 96 90 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 94 0.0 0 92 40 00 6.0 140 60 98 (Million Tonnes N) World capacity stagnates from 1998-2004 160 0.0 Net Change in World N Capacity World Nitrogen Supply MM Tonnes N 180 5.0 7 ra Calendar Years 10.0 ft ft 4.0 Calendar Years 10 196 — 2008 Integrated Crop Management Conference - Iowa State University Value of the U.S. Dollar World Natural Gas Prices ($/MMBtu) (Euros per $US) 14.0 10.0 1.20 W Europe U.S. Ukraine Russia 1.00 8.0 4.0 2.0 2004 2005 ft 0.90 6.0 0.0 “Dollar down over 40% since 2002” 1 10 1.10 2006 2007 0.80 0.70 0.60 J02 2008 J03 Nitrogen Project Listing 2009 2010 2007-10 Total Ghadir II Bahwan EBIC Acron Mopco J08 13 800 Urea 5,731 5,608 677 660 660 400 396 3,140 5,933 1,073 1,156 3,859 6,857 22,380 5,785 8,559 26,936 700 US $ 600 d d 2007 2008 Iran Oman Egypt Russia Egypt China Total J07 Middle East FOB Urea Priced - Local Currencies (000 Tonnes of Product) Ammonia J06 ra ra 11 Location J05 January 2004 - Current Calendar Years Country J04 ft 12.0 2008 Integrated Crop Management Conference - Iowa State University — 197 500 400 635 3,720 6,984 400 300 200 Euros 100 0 J04 12 J05 J06 J07 January 2004 - Current J08 14 198 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 199 U.S. Dry Urea Supply by Source Over-riding Market Fundamentals (MM Tons) Net Impact – Significant tightening in the world supply demand balance Canada Middle East China Venezuela Trinidad Other Total 2,032 976 0 38 297 264 3,607 1,749 2,148 1,175 431 472 579 6,554 -283 1,172 1,175 394 175 314 2,947 17 ($/Tonne) (MM Tons) “Imports now account for roughly 70% of total U.S. dry urea supply” d 850 10 0 10.0 650 Imports 6.0 550 450 02 03 04 05 06 07 08 5/ 29 6/ 19 7/ 10 7/ 31 8/ 21 9/ 11 10 /2 01 5/ 8 00 Yuzhny (Prills) 250 1/ 3 1/ 24 2/ 14 0.0 Middle East 350 3/ 27 4/ 17 Domestic Production US Gulf 3/ 6 4.0 2.0 “World import demand collapses (India followed by L. America, U.S.)” “World World prices jumped $200+ after China implemented export tax increase” d 750 8.0 99 Change World Urea Prices U.S. Dry Urea Supply 98 2008 ra ra 15 12.0 2000 ft ft  Strong World-wide growth in demand  Sharp reduction in new capacity from 2002-06  Dramatic decline in U.S. capacity since 2000  Escalating natural gas prices in NA/ W. Europe / E. Europe  Value of the U.S. Dollar  Record high freight rates Fertilizer Years 16 18 200 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 201 Chinese Urea Exports World Urea Trade (MM Metric Tons) (MM Tonnes) 7.0 18% 40 16% % of World Trade 6.0 R t off W Rest World ld 20% % of World Trade 30 12% 4.0 25% India 14% 5.0 “India now accounts for roughly 20% of world urea imports” 10% 15% ft 10% 6% 2.0 4% 1.0 10 5% 2% 0.0 0% 2002 2003 2004 2005 2006 2007 2008 0 0% 98 99 00 01 Calendar Years 05 06 07 08 21 (000 Product Tonnes) 400 1.6 July-Aug 2006 260 2007 307 2008 702 350 1.4 d 04 ra ra (MM Tons) d China Imposes Export Tax of 135% 300 250 0.8 200 0.6 150 0.4 100 Projected Average 0.2 2007 2008 50 0 D N O S A J J M A M F D J0 8 N 0.0 O 03 Brazil Urea Imports by Month Chinese Urea Exports 1.0 02 Calendar Years 19 1.2 ft 8% 3.0 20 J 20 F M A M J J A Calendar Year S O N D 22 202 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 203 U.S. Dry Urea Prices World UAN Exports ($/Ton) (MM Metric Tons) 900 6 800 700 Major world buyers return to the market? U.S. prices well below world prices Gulf Midwest 600 5 ROW 4 Sharp decline in world prices Slow start to the U.S. fall season 400 300 200 J S N J08 F A J A O D E. Europe /FSU 2 1 0 00 01 02 04 05 06 07 Calendar Years 23 25 ra ra 03 ft ft 3 500 U.S. UAN Imports U.S. UAN Supply d 15 Imports 12 9 Domestic Production 6 d (000 Tons UAN 32%) (000 Tons – 28%) Canada FSU E. Europe ROW Total 2006 2007 2008 % of Total 467 1,405 301 665 2,838 673 1,122 410 183 2,389 634 1,951 320 587 3,492 18.2% 55.9% 9.2% 16.8% 100.0% 3 “Two-thirds of U.S. UAN imports are sourced from Russia, Ukraine, Romania and other Eastern Bloc countries” 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 24 26 204 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 205 U.S. Ammonia Supply World UAN Imports (MM Metric Tons) (MM Tons) “Imports now account for roughly 45% of total U.S. supply” 24.0 Rest of World 22.0 20 0 20.0 18.0 16.0 W. Europe 14.0 Imports N. America 10.0 8.0 6.0 6 0 4.0 Domestic Production 2.0 0.0 98 99 00 01 Calendar Year 2007 02 03 06 07 08 29 ra ra 05 U.S. Ammonia Prices World UAN Prices ($/Ton) ($/Tonne 32%) 1,200 600 Black Sea Del. to U.S. Midwest Gulf 1,000 U.S. Gulf d d 04 Fertilizer Years 27 500 ft ft 12.0 800 400 600 300 200 400 100 200 0 J06 A J O J07 A J O J08 January 2006 - Current A J 0 O J04 28 J05 J06 J07 January 2004 - Current J08 J09 30 206 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 207 U.S. Ammonia Midwest – Gulf Price Differential ($/Ton) 500 Phosphate Situation & Outlook 400 J07 ft J06 J08 January 2003 - Current 33 ra ra 31 Disconnect Between Gulf & Midwest Markets DAP Prices – C. Florida and Export ($/Ton)  Distribution system was originally designed to move ammonia from U.S. plants to U.S. MW market  Limited ability to offload and ship imports to the Midwest  Pipeline & Barges system is currently fully utilized  Limited ability to increase rail  Tank space in the Midwest is being fully utilized with limited ability to increase thruput U.S. Export Price d d 1,100 900 FOB Central Florida 700 500 300 Net Impact – Midwest ammonia supply is for the most part fixed. 32 J M M N J0 7 S J 100 S J05 J J04 M J03 M 0 N J0 8 100 S 200 ft 300 34 208 — 2008 Integrated Crop Management Conference - Iowa State University World DAP/MAP Demand World Phosphate Supply Outlook (MM Metric Tons) MM Tonnes P2O5 2001-07 4.9% Growth 25 1990-2001 1 6% G 1.6% Growth th 20 2008 Integrated Crop Management Conference - Iowa State University — 209 60 % Capacity 90% Capacity Production Operating Rate 80% 45 70% 15 10 5 0 60% 50% 15 40% 30% 0 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 96 97 98 99 00 01 World DAP/MAP Demand 06 07 08 37 Estimated cost for non-integrated producer in India 800 d 700 Sulfur - Vancouver ($/LT) 500 Rock FOB Morocco (/$/tonne) d 600 400 10 300 Skyrocketing sulfur and rock prices have pushed 200 production costs up, especially for non100 integrated producers 0 J07 M M J 5 00 05 ($/Tonne) “Almost all of the growth has been in China and India” 15 0 04 Current Spot Rock & Sulfur Prices Rest of World India China 20 03 ra ra 35 25 02 Calendar Years Calendar Years (MM Metric Tons) ft ft 30 01 02 03 04 05 06 07 08 S N J08 M M J S Calendar Years 36 38 210 — 2008 Integrated Crop Management Conference - Iowa State University India DAP Production Cost - Imported Rock Central Florida DAP Prices ($/Tonne) 1,100 Upgrading 1,000 Ammonia 900 800 200 100 World DAP Imports “India now accounts for 30% of total world DAP trade” d 14.0 Potash Situation & Outlook d 12 0 12.0 10.0 Rest of World 8.0 6.0 41 ra ra 39 (MM Tonnes P2O5) ft Sep 08 Demand D dd destruction? t ti ? 300 J Sep 07 400 A Sep 06 500 O J0 8 200 600 J 400 ft 600 0 High production cost for non-integrated producers Reduced production in major exporting countries 700 800 A Sulfur O J0 9 Rock A 1000 1,200 O J0 7 1200 ($/Ton) J 1400 2008 Integrated Crop Management Conference - Iowa State University — 211 4.0 India 2.0 0.0 2002 2003 2004 2005 Calendar Years 2006 2007 2008 40 42 212 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 213 KCI ($US/short ton) Potash Production Capacity Growth (Million Tonnes/Yr KCl) Mid-West Average $1,000 75 $900 $800 60 $700 $600 70.5 61.3 Other China Mid-East Europe 45 $500 $400 Russia 15 Canada 0 2007 2012 Fertilizer Years World Potash Production and Trade Average U.S. Corn Budget (Million Tonnes KCl) ($/Acre) 60 2008 2009 138 153 145 147 Price ($/bu) $3 22 $3.22 $3 60 $3.60 $4 34 $4.34 $4 20 $4.20 Value of Production $444 $551 $629 $616 Seed $44 $45 $57 $62 Fertilizer $80 $88 $97 $198 Chemicals $24 $ $24 $ $28 $ $29 $ Fuel, Lube, Electricity $29 $31 $43 $50 Variable Cost: 20 10 2007 2006 2005 2004 2003 2002 2001 0 2000 2007 d d Trade 30 2006 Yield (bu/pltd ac) Production 40 45 ra ra 43 50 ft Jan08 Jul-0 8 Jul-0 Jan05 Jul-0 5 Jan06 Jan04 Jul-0 4 2 Jan03 Jul-0 3 Jul-0 Jan01 Jul-0 1 Jan02 Jan00 Jul-0 0 $100 $0 6 Jan07 Jul-0 7 $300 $200 ft Belarus 30 Other ______ ______ ______ ______ Total Calendar Years 44 Value less variable cost $206 $218 $314 $372 $238 $333 $315 $244 46 214 — 2008 Integrated Crop Management Conference - Iowa State University U.S. Planted Acreage Average U.S. Soy Budget 2006 Yield (bu/pltd ac) 2007 2008 (MM Acres) 2009 45.9 44.6 45.8 46.4 Price ($/bu) $5 54 $5.54 $9 62 $9.62 $11 91 $11.91 $8 60 $8.60 Value of Production $254 $429 $546 $399 Variable Cost: Fertilizer Chemicals C Fuel, Lube, Electricity $35 $42 $46 $11 $12 $20 $25 $14 $ $15 $ 5 $15 $ 5 $16 $ 6 $16 $17 $24 $27 2008 2009 Change 2008-09 93.6 60.4 64.7 10.8 91 9 91.9 321.4 87.0 63.0 75.9 9.4 91 7 91.7 327.0 89.0 59.9 76.5 9.1 90 0 90.0 324.5 2.0 -3.1 0.6 -0.3 -1 7 -1.7 -2.5 ______ ______ ______ ______ Total $79 $101 $114 $179 $350 $445 $285 ra Value less variable cost $75 47 2009 Avg. U.S. Corn vs. Soy Comparison Corn (MM Nutrient Tons) Soy 147 46.4 P i ($/bu) Price ($/b ) $4 20 $4.20 $8 60 $8.60 Value of Production $616 $399 $62 $46 $198 $25 Chemicals $29 $16 Fuel, Lube, Electricity $50 $27 ______ ______ $372 $114 $244 $285 d Yield (bu/pltd ac) U.S. NPK Fertilizer Demand – FY09 Variable Cost: Seed Fertilizer Other Total Value less variable cost 2007 2008 2009 Change 08-09 13.2 12.9 12.9 0.0% Phosphate 4.6 4.5 4.1 -9.0% Potash 51 5.1 50 5.0 45 4.5 -10 0% -10.0% 22.9 22.4 21.6 -3.6% d ($/Acre) 49 ra Other $34 ft Seed Corn Wheat Soybeans Cotton Other Total Acres 2007 ft ($/Acre) 2008 Integrated Crop Management Conference - Iowa State University — 215 Nitrogen Total 48 50 216 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 217 Managing nitrogen for optimum profit and minimum environmental loss Gyles Randall, Professor, Crop and Soil Sciences, University of Minnesota ft With volatile crop and nitrogen prices, greater environmental concerns and awareness, and increasing efforts to minimize risk, farmers are searching for information to establish an effective and profitable N management game plan. However, the N management game plan is not simple. It becomes complex as various uncontrollable soil and weather factors are involved as well as the controllable factors of N rate, time and method of application, N source, nitrification inhibitors, etc. Best management practices (BMPs) for N are broadly defined as economically sound, voluntary practices that are capable of optimizing profitability, minimizing the loss of nitrate to surface and ground water, and reducing risk. In Minnesota, BMPs have been identified for various areas of the state depending on climate, soil, and geologic features. Management practices are placed into three categories: (1) Recommended ra (2) Acceptable, but with greater risk (3) Not recommended The risk issue can be either economic (higher cost of N product or slightly reduced economic return) or environmental (unpredictable but problematic increase in nitrate loss). The results of various N research studies in southern Minnesota on Nicollet-Webster clay loam soils at Waseca and Port Byron silt loam soils in Olmsted Co. will provide the decision-making information in this paper to assist growers and dealers in developing their N management game plans. Rate of N application d d ra ft Introduction Using the correct amount of N optimizes crop yield while minimizing loss of N to the environment. Using the wrong amount reduces profitability for the farmer and can result in excess nitrate being delivered to ground and surface water resources. The effect of N rate on corn yield, N use efficiency, profitability, and nitrate loss to tile drainage is shown in Tables 1 and 2. Compared with the standard 120-lb N rate applied in the fall, adding an additional 40 lb N/A (160-lb N rate) increased yields 6 bu/A (4%), decreased profit by $4/A (3%), and increased NO3-N concentration in the tile water by 4.9 mg/L (37%). On the other hand reducing the N rate to 80 lb/A reduced yield 22 bu/A (13%) reduced profit $60/A (47%), and reduced NO3-N concentration in the water by 1.7 mg/L (13%). Greatest yield and profit with a minimal increase in NO3-N concentration was found with the spring-applied 120-lb N rate. Moreover, fertilizer N use efficiency (NUE) was optimized at 0.58 bu/pound of fertilizer N compared to 0.39 for the 160-lb N rate and 0.42 for the 80-lb rate. Using total N to determine NUE was not an appropriate measure because 61% of the maximum yield obtained (180 bu/A) was provided by the soil (110 bu/A). These data clearly demonstrate the importance of using the correct N rate as a cornerstone BMP from an economic and a water quality perspective. 218 — 2008 Integrated Crop Management Conference - Iowa State University N-Serve lb N/A N Use Efficiency Total N Fert. N Net return to N4/ bu/A bu/lb total N bu/lb fert. N $/A 2/ 3/ -- -- 110 -- -- -- 80 Fall + 144 1.8 0.42 72. 120 “ + 166 1.4 0.47 132. 120 “ - 165 1.4 0.46 136. 160 “ + 172 1.1 0.39 128. 120 Spr. + 180 1.5 0.58 188. 120 “ - 180 1.5 0.58 196. ft 0 1/ Application time ranged between Oct. 22 and Oct. 31 with the 6” soil temp in the 10 days following application ranging from 38º to 50ºF. 2/ bushels of corn per lb total N (soil N, 0-lb control plot + fertilizer N). 3/ bushels of corn per lb of fertilizer N. ra 4/ Based on corn = $4.00/bu, N = $0.70/lb, and N-Serve = $8.00/A. Table 2. Nitrate-N concentrations and losses in tile drainage water as affected by N rate, time of application and N-Serve for corn after soybeans at Waseca, 2000-2004. N application Rate N-Serve Time lb N/A NO3-N Lost Corn mg/L Soybean Total - - - - lb NO3-N/A/4 yr - - - - 80 Fall + 11.5 115 90 205 120 “ + 13.2 121 99 220 160 “ + 18.1 142 139 281 120 Spr - 13.7 121 98 219 d 1/ Flowweighted NO3-N conc.1/ Across four C-Sb cycles, i.e. four years of corn followed by four years of soybean. Time of application and N-Serve A 4-yr study at Waseca, comparing a late-October application of anhydrous ammonia at three N rates plus N-Serve with spring-applied ammonia without N-Serve, showed a 14 bu/A yield response and $64/A economic return advantage for spring application when applied at the 120lb rate with no difference in flow weighted NO3-N concentration in the tile drainage (Tables 1 and 2). Moreover, the 120-lb spring N treatment increased yields 8 bu/A and economic return to N by $68/A while decreasing NO3-N concentration in the drainage from 18.1 to 13.7 mg/L (24%) compared with 160 lb N/A + N-Serve applied in the fall. Conversely, choosing to apply 160 lb N/A in the fall rather than 120 lb/A in the spring would cost the grower a 4% yield and 35% economic reduction while increasing nitrate losses in drainage by 32%. A long-term study, comparing late-October application of ammonia with and without N-Serve with a spring pre-plant application without N-Serve, showed distinct yield, economic, and environmental advantages for spring application, but not in all years (Table 3). Across the 15yr period, corn yields averaged about 10 bu/A greater for the fall N + N-Serve and spring N treatments compared with fall N without N-Serve. Also, compared with fall application of N without N-Serve, NO3-N losses in the drainage water were reduced by 14 and 15%, economic return to N as increased by $28 and $48/A, and N recovery in the grain was increased by 8 and 9% for fall N + N-Serve and spring N, respectively. However, corn yields were significantly affected by the N treatments in only 7 of 15 years. In those seven years, when April, May and / or June were wetter-than-normal, average corn grain yield was increased by 15 and 27 bu/A and average economic return was increased by $52 and $108/A for the fall N + N-Serve and spring N treatments, respectively. In summary, the 15-yr data suggest that applications of ammonia in the late fall + N-Serve or in the spring preplant were BMP’s. However, when spring conditions were wet, especially in May and June, spring application gave substantially greater yield and profit than the fall N + N-Serve treatment. Therefore, fall N + N-Serve application is considered to be more risky than a spring, preplant application of ammonia. Moreover when N-Serve was not used, fall application of ammonia was more risky (lower yields) compared with spring application regardless of tillage system (no-till, strip-till, spring field cultivate, and fall chisel plow). ft Time Grain yield ra Rate 1/ Nitrate lost in tile drainage over the 4-yr period for the 160-lb rate was consistently greater for both the corn phase and soybean phase of the rotation (Table 2). During the corn phase, nitrate losses were 17% greater for the 160-lb rate compared to the 120-lb spring rate, while in the soybean phase nitrate losses were 40% greater for the 160-lb rate. This clearly indicated that considerably more N from the 160-lb N rate applied in the fall before corn remained in the soil as residual nitrate at the end of the corn year. This nitrate was then flushed out in the following year when soybeans were planted (about 18-20 months after application). In these four cycles of the corn-soybean rotation, 45% of the total NO3-N lost from the rotation occurred during the soybean phase for the 80 and 120-lb N rates while 50% was lost in the soybean phase for the “excessive” N rate (160 lb N/A). Table 3. Effect of time of application and N-Serve on corn yields, economic return and flow-weighted nitrate-N in tile water at Waseca, 1987-2001. d Table 1. Corn grain yield, nitrogen use efficiency (NUE), and net return to N as affected by rate and time of N application and N-Serve for corn following soybeans at Waseca, 2000-03. N application 2008 Integrated Crop Management Conference - Iowa State University — 219 Time of N Application Parameter Fall Fall + N-Serve Spring 144 153 156 -- $28 $48 14.1 12.2 12.0 131 146 158 7-Yr Avg. Economic return over fall N($/A/yr) -- $52 $108 Nitrogen recovery in corn grain (%) 38 46 47 15-Yr. Avg. Yield (bu/A) 15-Yr Avg. Economic return over fall N ($/A/yr) 1/ 15-Yr Avg. FW NO3-N Conc. (mg/L) 7 Yr Avg. Yield (bu/A)2/ 1/ 3/ Based on N @ $0.70/lb N; N-Serve = $8.00/A; Corn = $4.00/bu. Only those seven years when a statistically significant yield difference occurred among treatments. 3/ Nitrogen recovery in the corn grain as a percent of the amount of fertilizer N applied. 1/ 2/ 220 — 2008 Integrated Crop Management Conference - Iowa State University ft Nitrogen source must also be considered when selecting the proper time of application. A study at Waseca evaluated late October application of urea (4” deepband) and anhydrous ammonia with and without N-Serve compared to spring preplant urea and anhydrous ammonia. Threeyear average yields show a 33 bu/A advantage for urea and a 14 bu/A for ammonia when applied in the spring (Table 4). Nitrogen recovery in the corn plant ranked: spring ammonia = spring urea >fall ammonia>fall urea. The effect of N-Serve in this study was minimal. Yield responses to the spring treatments were greatest in 1998, when April and May were warm and late May was wet, and in 1999 when the fall of 1998 was warm and April and May 1999 were very wet. Significant yield differences were not found in 1997 when the fall of 1996 was cold and the spring of 1997 was cool and dry. Table 5. Corn yield following soybeans as affected by time/method of application for two tillage systems at Waseca, 2001-2003. Nitrogen Treatment Time % No 152 43 ra “ “ Yes 158 47 “ An. Ammonia No 168 60 “ “ Yes 170 63 Spr. Preplant Urea No 185 76 “ An. Ammonia No 182 84 -- None -- 112 -- LSD (0.10): 8 d Split application studies were conducted at Waseca from 2001-03 to evaluate various methods of applying urea-ammonium nitrate solution (28%, UAN) at planting time in combination with a V3 sidedress treatment. The split treatments were compared with single fall and preplant applications of N in two tillage systems (spring field cultivate and strip-till) for corn after soybeans. Three-yr yield averaged were generally greatest for the split treatments where UAN was either dribbled 2 inches from the row at planting or broadcast with a herbicide immediately after planting (weed and feed) in combination with 60 to 80 lb N/A sidedress injected midway between the rows at V3 to V4 stage (Table 5). Lowest yields occurred with a single preplant application of UAN in the spring field cultivate system and either fall ammonia + N-Serve or 40 lb N/A dribbled as UAN at planting next to the seed row in the strip tillage system. Perhaps the 40-lb rate was too high when placed this close to the seed row in the strip-till system. Nitrogen recovery in the plant ranged from 56% for the fall ammonia treatments to 71% for the “weed and feed” UAN treatments when averaged across tillage systems. These results suggested substantial flexibility exists for combinations of preplant, planting, and sidedress applications of N as alternatives to traditional fall-applied ammonia. 2/ 3/ Yield (bu/A) -- 122 111 Fall AA 100 Yes 167 161 Spr. AA 100 No 165 168 Spr. Urea 100 “ 167 166 UAN 100 “ 161 -- Plant + SD “ 20 + 80 “ -- 170 “ “ 40 + 60 “ 174 163 Pre-emerg3/ + SD “ 40 + 60 “ 172 174 2/ 1/ ST1/ 0 1/ SFC = spring field cult., ST = strip till, SD = sidedress at V3-V4 stage. Dribbled 2” from row at planting Broadcast pre-emergence with herbicide (weed and feed). Experiments containing various rates of preplant N and combinations of preplant plus sidedress N at various mid- to late-season times (V6 to V12) were conducted at 12 non-irrigated sites in 2004-2007. Unless noted differently in Table 6, preplant N was broadcast-applied as urea and the sidedress treatments were injected as UAN mid-way between the rows. Preplant rates were usually 30 lb N/A following soybeans and 40 lb N/A following corn. Corn yields for the splitapplied N treatments were less than the preplant-applied treatments in 11 of the 17 rotation-SD time-site comparisons. Split-applied N gave greater yields (+1 to +14 bu/A) in five comparisons with no difference between preplant and split N in one comparison. Averaged across the 17 comparisons, yields were reduced 6 bu/A by split applications where sidedress N was applied mid- to late-season (V6 to V12). These results indicate that split-applying N does not consistently generate yield improvement over preplant N under rain-fed conditions as previously assumed. Two factors, one controllable and one not, appear to cause these yield reductions. The dominant one is weather, in particular a 2 to 3-week period without rain shortly after sidedress application can lead to marked N-deficiency because the N does not move down into the root system. The other factor is inadequate amount of preplant N to sustain corn development until the plant intercepts and takes up the sidedress N. In the future, we may find farmers applying 60 to 80% of their anticipated N needs prior to planting and then applying the remainder in June, using various diagnostic criteria and adaptive management practices to help make the sidedress N rate decision. ra bu/A SFC -- d N Recovery Urea N-Serve N-Serve -- Spr. 3-Yr Average Yield Fall Source Rate lb N/A Table 4. Corn yield and N recovery in the whole plant as influenced by time of application and N source at Waseca, 1997-1999. Time Source Tillage System 1/ ft Time of application and N source Nitrogen Management 2008 Integrated Crop Management Conference - Iowa State University — 221 222 — 2008 Integrated Crop Management Conference - Iowa State University Table 6. Corn yield responses from mid and late sidedress N compared to preplant applications in southern Minnesota, 2004-2007. Corn yield Total N rate applied 1/ Site Rotation SD Time lb N/A 120 avg. V8 181 0 04-1 CC 120 avg. V12 181 -2 05-1 CS 105 avg. V9 151 +1 05-1 CS 105 avg. V122/ 151 -1 05-2 CC 160 V6 174 +14 ft 2/ Grain yield lb N/A bu/A lb N/A bu/lb N3/ bu/lb FN4/ % None 0 118 80 -- -- -- -9 UAN (28%) 60 173 124 2.9 0.92 73 213 -5 “ 90 189 142 2.1 0.79 68 V6 191 -19 “ 120 198 156 1.3 0.67 63 90 V6 195 -9 “ 150 202 167 1.3 0.56 58 CS 90 V7 1814/ -5 60 164 115 2.7 0.77 57 07-1 CS 90 V123/ 1814/ -53 UAN + eNhance 07-2 CC 100 avg. V8 155 +4 “ 90 182 132 2.0 0.71 58 07-3 CC 120 avg. V6 184 +5 120 195 150 1.6 0.64 58 07-3 CS 90 avg. V6 214 +1 150 197 157 1.3 0.53 51 High NRG-N 60 155 108 2.6 0.62 45 “ 90 160 114 1.8 0.47 37 120 180 128 1.5 0.52 40 150 186 145 1.2 0.45 43 CC 120 avg. V102/ 167 -9 06-1 CS 90 V7 1974/ -2 06-1 CS 90 V123/ 1974/ -13 06-2 CC 100 avg. V7 195 06-3 CS 90 avg. V6 06-4 CS 90 06-5 CS 07-1 avg. = average of N rates with same time of SD application, i.e. 90+120+150=120 or 90+120=105 applied next to row as urea + Agrotain. dribble-applied next to row as UAN (28%). injected midway between rows as UAN (28%) at V2 stage. Nitrogen sources We have all heard the statement “a pound of N is a pound of N”; but we know that statement is not always true. Prolonged wet conditions can exert substantial denitrification potential in poorly drained soils, causing greater denitrification losses of UAN and urea compared to anhydrous ammonia. In other cases, different formulations of or coatings on standard products may cause performance differences. In the last two years we have conducted experiments following soybeans at Waseca to determine if performance varies among three fluid N fertilizers [UAN (28%), UAN + eNhance, and High NRG-N]. These fluid fertilizers were injected mid-way between the rows at the V2-V3 stage using the target N rates shown in Table 7. Grain yields were clearly greater for UAN (28%) compared to High NRG-N. Apparently, the 40% availability enhancement suggested by the manufacturer did not occur in this trial. In fact, the yield for the 150-lb target rate of High NRG-N (186 bu/A) Source “ “ “ “ Nitrogen use efficiency ft Target rate 05-3 1/ ra 4/ Table 7. Corn grain yield, total N uptake, N use efficiency, and apparent N recovery as affected by source and rate of fluid N at Waseca, 2006-07. Total plant N uptake2/ d 3/ Split Adv/ Disadv. is almost identical to the 40% lower rate (90 lb N/A) of UAN (28%) (189 bu/A). Yields for UAN + eNhance were only slightly lower than for UAN (28%). Total plant N uptake and apparent fertilizer recovery by the corn were also ranked: UAN (28%) > UAN + eNhance >> High NRG-N. Nitrogen use efficiency in terms of bushels of corn per pound of fertilizer N (target rate) was consistently greatest for UAN (28%) and least for High NRG-N. Note that the NUE was also greatest at the lowest N rate but decreased to about 0.55 bu/lb FN near the economic optimum N rate. Nitrogen use efficiency in terms of bushels of corn per pound of total N (soil + fertilizer) was meaningless because 58% of the N needed for the highest corn yield was met by soil N (118 bu/A produced only with soil N). d 2/ CC ra 1/ PP - - - - - bu/A - - - - - 04-1 2008 Integrated Crop Management Conference - Iowa State University — 223 Apparent5/ FN recovery Target rate of N availability. UAN + eNhance and High NRG-N were applied at rates of 20% and 40% lower, respectively, due claims that their enhanced N availability would match these target rates. 2/ Total N in the above-ground plant. 3/ bushels of corn per lb of soil N (0-lb check plot) + fertilizer N (FN). 4/ bushels of corn per lb of fertilizer N (FN). 5/ (Total plant uptake in treatment – total N uptake in 0-N check plot) ¸ FN applied. 1/ Because of increasing concerns over the future of fall application of N, a study comparing early spring applications of three N sources [anhydrous ammonia (AA), urea, and UAN (28%)] was started at Waseca. Corn grain yields shown in Table 8 dramatically indicate a 28 bu/A difference among the three sources. Little difference was found in these two years between AA and urea, but corn fertilized with UAN yielded significantly less in both years, especially when broadcast preemergence and not incorporated. Volatilization of the UAN left on the soil surface is considered to be the primary loss mechanism. However, the lower yields with preplant, broadcast and 224 — 2008 Integrated Crop Management Conference - Iowa State University incorporated UAN suggests other factors as well. In both years, surface soils were saturated for about a week around June 1. Perhaps denitrification occurred in this organic-rich top 2 to 4” of soil, causing N loss. Table 8. Corn grain yield as influenced by various N sources applied in the early spring for corn after soybeans at Waseca, 2007-2008. N Management1/ N Source Time N-Serve were greater when spring-applied. In south-central Minnesota, late fall or spring preplant ESN is regarded as an “acceptable BMP, but with greater risk” (economic), while fall-applied urea is “not recommended”. Mixtures of ESN and urea might be appropriate, but they have not been evaluated on corn yet. Table 10. Corn yields as influenced by fall vs. spring application of urea and ESN for corn after soybeans at Waseca, 2003-2007. Application Time1/ 2-Yr Avg. Yield Source bu/A - - - - 5-yr Yield avg. (bu/A) - - - - An. Ammonia Preplant No 178 Urea 182 186 “ “ Yes 178 ESN 190 185 Urea Preplant, incorp. No 186 UAN (28%) “ “ No 165 “ Pre-emergence No 158 d Source Time 3-Yr. Avg.1/ Yield bu/A Urea Preplant 152 UAN (28%) “ 146 “ Split2/ 150 Averaged across 60, 90, 120, 150, and 180-lb N rates. 30 lb N/A preplant and rest injected at V4 stage. ESN produced by Agrium is a polymer-coated urea with controlled release properties. Research has been conducted for five years at Waseca, MN to determine the efficacy of fall and springapplied ESN as a viable source of N. ESN and urea were applied about Nov. 1 each year following soybeans and preplant in the following spring (mid-April). Corn yields shown in Table 10 indicate ESN to be a superior product to urea when both are fall-applied. When spring-applied, yields were similar for both N sources. In general, corn yields were slightly greater when ESN was applied in the fall compared to spring, but when urea was used, yields Improving nitrogen use efficiency (NUE) and fertilizer N recovery Historically, NUE and the recovery of FN in the plant have been markedly lower than desired when applying N at economically optimum rates. With growing environmental concerns, i.e. water quality (nitrates) and air quality/global warming (nitrous oxide), significant emphasis has been placed on improving NUE and recovery of FN in the crop. As new hybrids posses genetic traits such as corn rootworm resistance, which theoretically may possess larger and more efficient root systems, interest has developed to determine if NUE and FN recovery can be improved by hybrids having these pest resistance traits. ra N Treatment Applied at 100 lb N/A and incorporated. Studies were conducted on second-year corn and corn after soybeans, at Waseca, MN in 2006 and 2007 to determine if grain yield, NUE, and apparent fertilizer N recovery were influenced by genetic traits (double stack, glyphosate + corn borer resistance vs. triple stack, glyphosate + corn borer + corn rootworm resistance) and N management (preplant vs. split-applied N). Two-year data, which is considered preliminary at this time, suggests that grain yields were improved 4 to 9 bu/A with the triple stack hybrids, even on the zero-N plots, but were not affected differently by preplant vs. split N application. NUE and apparent FN recovery in the plant were negligibly affected by the trait characteristics (due to greater yields for the zero-N plots as well as the N fertilized plots) and N application method (preplant vs. split). d N was applied at 100 lb N/A. 1/ ft 118 ft -- Table 9. Continuous corn yield as affected by source and time of N application in Olmsted Co., 2002-2004. 2/ Spring (mid-April) -- A 3-year study was conducted on a silt loam soil in Olmsted Co. to determine if N source [urea vs. UAN (28%)] and application time (preplant vs. split) affected corn yields. The average corn yields shown in Table 9 (a product of 3 years x 4 replications x 5 N rates = 60 observations per yield average) clearly show greater yields with preplant urea compared to preplant UAN when both are incorporated immediately by field cultivation. For these reasons, preplant UAN is considered an “acceptable practice, with greater risk” in Minnesota’s BMPs for N. 1/ Fall (Nov. 1) None ra 1/ 2008 Integrated Crop Management Conference - Iowa State University — 225 Manure Nitrogen management from fall-applied hog manure has also been a challenge on the poorly drained (but tiled) Webster clay loam soils at Waseca. A set of nine individually isolated tile drainage plots was used to accommodate three treatments (zero-N, fall-applied hog manure, and spring-applied urea) from 1998-2001. The purposes were to determine: (1) if nitrate and phosphorus losses into tile drainage were different among the three treatments and (2) whether N management for continuous corn was different between liquid hog manure and urea N sources. Hog manure from a finishing barn was broadcast-applied and incorporated within four hours around Nov. 1. Based on the application rate, manure-N analyses, and the assumptions that 75% of the total N was available in year 1 and 15% of the total N was available in year 2, 226 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 227 References Corn yields were not significantly different between the manure and urea treatments in 1998 and 2000 (Table 11). But in 1999 and 2001, yields were 35 to 40 bu/A greater for the urea treatment. Nitrate and P losses via the tile drainage water were not different between the two N sources (data not shown). Examination of spring rainfall characteristics explains why fall-applied hog manure to continuous corn performed so badly in 3 of 4 years. In 1998, spring rainfall for AprilJune was within an inch of normal and yields were high for both N sources. In 1999 and 2001, spring rainfall was 5 to 8” above normal for the two periods shown in Table 11. Under those conditions, N from the hog manure applied to the corn residue and incorporated by moldboard plowing was apparently denitrified and yields were substantially reduced. Corn yields from the urea plots were not affected; perhaps due to the late April application and incorporation into the top 2-3” where denitrification was as not prevalent. In 2000, when more than 20” occurred between mid-May and mid-July (after nitrification of both urea and hog manure was complete), severe denitrification occurred and N was lost from both N sources. These data indicate that N availability from fall-applied hog manure can be problematic especially when applied for continuous corn. Under prolonged, wet conditions, such as occurred in Iowa in 2008, one could expect significant loss of N from fall-applied hog manure and subsequent N deficient, lower yielding corn. Randall, Gyles, George Rehm, and John Lamb. 2008. Best management practices for nitrogen use in southeastern Minnesota. 8 pp. Univ. Minnesota Extension Service. Pub. # 08557. www.extension.umn.edu/distribution/cropsystems/DC8557.pdf Available Year N applied Hog Zero-N lb/A Manure Urea Spring rainfall - - - - - - - bu/A - - - - - - 210 57 173 178 “Normal” =11.9”, 4/1-6/30 1999 260 68 147 182 11.8” from 4/1-5/31 2000 230 68 142 140 >20” from 5/18-7/15 2001 208 66 134 174 16.2” from 4/1-6/15 d 1998 Summary The above research information clearly emphasizes the many factors affecting the complexity of N management. When temps are normal and rainfall is normal or slightly drier, N management is much less complex than if temps are either much cooler or warmer-than-normal and spring rainfall is excessive. Because weather for the upcoming season cannot be predicted or controlled, growers and nutrient suppliers are encouraged to choose controllable N management practices that minimize economic and environmental risk, allowing greater long-term profitability. Sawyer, John E. and Gyles W. Randall. 2008. Nitrogen rates. p. 59-71. In Final Report: Gulf Hypoxia and Local Water Quality Concerns Workshop. Published by the Upper Mississippi River Sub-basin Hypoxia Nutrient Committee. 26-28 Sept. 2005. Ames, IA. ft Randall, Gyles W. and John E. Sawyer. 2008. Nitrogen application timing, forms, and additives. p. 73-85. In Final Report: Gulf Hypoxia and Local Water Quality Concerns Workshop. Published by the Upper Mississippi River Sub-basin Hypoxia Nutrient Committee. 26-28 Sept. 2005. Ames, IA. Randall, G. W. and J. A. Vetsch. 2005. Corn production on a subsurface-drained mollisol as affected by fall versus spring application of nitrogen and nitrapyrin. Agron. J. 97:472478. Randall, G. W. and J. A. Vetsch. 2005. Nitrate losses in subsurface drainage from a corn-soybean rotation as affected by fall and spring application of nitrogen and nitrapyrin. J. Environ. Qual. 34:590-597. ra Table 11. Continuous corn yields as influenced by fall-applied hog manure vs. spring-applied urea at Waseca, (19982001). Randall, Gyles, George Rehm, John Lamb, and Carl Rosen. 2008. Best management practices for nitrogen use in south-central Minnesota. 8 pp. Univ. Minnesota Extension Service. Pub. # 08554. www.extension.umn.edu/distribution/cropsystems/DC8554.pdf Randall, G. W., J. A. Vetsch, and J. R. Huffman. 2003. Corn production on a subsurface-drained mollisol as affected by time of nitrogen application and nitrapyrin. Agron. J. 95:12131219. Randall, G. W., J. A. Vetsch, and J. R. Huffman. 2003. Nitrate losses in subsurface drainage from a corn-soybean rotation as affected by time of nitrogen application and use of nitrapyrin. J. Environ. Qual. 32:1764-1772. Randall, G.W., and D.J. Mulla. 2001. Nitrate nitrogen in surface waters as influenced by climatic conditions and agricultural practices. J. Environ. Qual. 30:337-344. d ra ft the amount of “available” N was calculated each fall. Urea was broadcast and incorporated the next spring at the equivalent “available” N rate from the previous fall application of manure. Corn grain and silage yields, N uptake, and nitrate and phosphorus losses in tile drainage were measured. Randall, G.W., and M.J. Goss. 2008. Nitrate losses to surface water through subsurface, tile drainage. pp. 145-175. In R.F. Follett and J.L. Hatfield (Eds.) Nitrogen in the environment: sources, problems, and management (second edition). Elsevier Science B.V., Amsterdam. 228 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 229 Comparison of spring applied ESN and urea as sources of nitrogen for corn production J.A. Moore, Graduate Research Assistant, Agronomy, Iowa State University R. Killorn, Professor, Agronomy, Iowa State University M. Gonzalez, Graduate Research Assistant, Agronomy, Iowa State University ft The use of nitrogen (N) fertilizer to obtain profitable corn grain yields is very common in Iowa. Proper N fertilization is a difficult challenge facing today’s crop producers. Rising costs of N fertilizer encourage producers to look for ways to increase yields and recover applied N while keeping costs at a minimum. ra Nitrogen is subject to physical and biological processes in the soil which can influence the amount of N that is available for plant uptake (Gonzalez, 2005). Urea (CO(NH2)2) is one of the most common dry N fertilizers used in the United States today. When urea is applied to soils, it is hydrolyzed rapidly by urease to form ammonium (NH4+) and is then converted to nitrate (NO3-) by a process called nitrification. Leaching of applied N fertilizer results in reduced uptake efficiency by the target crop and is an agricultural problem that crop producers have to deal with (Wang and Alva, 1996). The dominant form of N in well-aerated soils is NO3--N, which is easily lost to leaching when water passes through the soil profile (Allen, 1985). ESN is a controlled-release N product (44% N) developed by Agrium, Inc. When ESN comes in contact with soil moisture, it absorbs water and liquefies the urea inside of a coating. ESN releases liquid urea through its polymer coating during the growing season. As temperature increases, the rate of release of the urea into the soil solution increases. Slow and controlled-release fertilizers are predominately used in the turf grass and horticultural industries because of their higher cost when compared to conventional fertilizers (Hauck, 1985). The use of controlled-release fertilizers offers advantages such as reduced passes over the field, decreased plant injury, and soil properties (pH, soil texture, microbial activity, etc) don’t affect release rates of the fertilizer (Trenkel, 1997). Currently the cost of the fertilizer is prohibiting its use in lower value crops such as corn. Handling of the product is also an issue. Care must be taken not to compromise the integrity of the coating which can make the fertilizer lose its controlled release characteristics. To date, little research has been published comparing ESN with urea for application to corn. d d ra ft Introduction The objectives of this study were to: 1) compare the effects of spring-applied ESN and urea on corn grain yield and 2) compare the effects of spring-applied ESN and urea on soil NH4+-N and soil NO3--N concentrations at three times during the year: the V-6 growth stage, the V-15 growth stage, and at post-harvest. Materials and methods A study was conducted over five growing seasons at two locations in Iowa: the Northern Research and Demonstration Farm (KNW) at Kanawha (2003-2007) and the Northwest The corn was scouted several times throughout the growing season to evaluate overall plant health and possible damage due to insects, disease, and weather related events. Grain Yield and Analysis ra The center rows of each plot were harvested (three rows at Kanawha and two rows at Sutherland) with a combine. The weight of the grain in each plot and moisture content were recorded when harvested by the combine. A sub-sample of the grain was collected, weighed, and dried at 60º C. The sub-sample was used to determine grain moisture content. Corn grain yield was adjusted to reflect a moisture content of 155 g kg-1. d Chemical analysis of the grain was conducted as follows: A 0.25g sub-sample of grain was ground, dried for a minimum of twenty-four hours, and was digested using the Hach Digesdahl® Digestion Apparatus, and the Hach Plant Tissue and Tissue Analysis System (Hach Company, 1988), with concentrated sulfuric acid (18 M H2SO4) and 50% hydrogen peroxide (H2O2). The digested product was then used to determine percent N by using a modified Nessler Method test and a Hach DR/3000 Spectrophotometer (DR/3000 Procedure Code N.10) as described in the method for Nitrogen Analysis in Total Plant Tissue (Hach Company, 1988). Nitrogen uptake was calculated by multiplying the grain yield by the percent of N in the grain. Soil Sampling and Analysis Soil samples were collected three times a year at each site and year in 2005-2007. The soil samples were taken at the V-6 growth stage, the V-15 growth stage, and after harvest. Three cores were randomly taken to a depth of 30 cm between the center two rows of the plot and combined to form the sample. The post harvest sample included samples collected from a depth of 31-60 cm. The soil samples were dried at 60º C for a minimum of twenty-four hours and ground to pass through a 2 mm sieve. A 10 g sub-sample was weighed and extracted with 50 ml of 2 M KCl solution. The extract was filtered and analyzed for NO3--N and NH4+-N using a QuikChem 8000 Automated Ion Analyzer by the QuikChem Method 12-107-04-1-B (Lachat Instruments, 1992) for the NO3--N and QuikChem Method 12-107-06-2-A (Lachat Instruments, 1993) for NH4+-N. Data Analysis Statistix 8 (Analytical Software, 2003) was used to analyze the data. The analyses for each combination of site and year were done separately. Nitrate-N and NH4+-N content for all soil sampling times were also analyzed separately. Differences at the p>F = 0.05 level or less were considered significant. Outliers in all of the data, except for corn grain yield, were identified by using residual graphs and were determined to be non-representative if they were greater than three standard deviations from the experiment mean. Results and discussion Kanawha location Grain production Corn grain yield increased with N rate each year of the study (p>F = <0.0001) (Table 4). The difference between the two materials in 2003, 2006, and 2007 were not statistically significant. In 2004 and 2005, there was no response to material (p>F = 0.0646) and (p>F = 0.0671) (Figures 1, 2) (Table 4), but there was a trend for ESN to out-yield urea treatments (Figures 1, 2). The interaction between material and N rate was not significant in any year of the study. In 2007, ESN treatments had a higher average grain yield than urea treatments. Over the five site-years, there was variability in the grain yields. We think that this could be due to different weather and soil conditions over the site-years. ft ft Treatments were arranged as a factorial in a randomized complete block design with four replications. Each experimental plot measured 4.6 m by 12.2 m at KNW and contained six rows of corn spaced 76 cm apart. The experimental plots at NW measured 3.05 m by 12.2 m. These plots contained 4 rows of corn spaced 76 cm apart. The ESN (44% N) and urea (46% N) were hand applied in the spring before the corn was planted and incorporated within twenty-four hours of application to reduce N loss due to volatilization. Nitrogen application rates for all sites in all years were: 0, 34, 67, 101, 134, 168, and 202 kg N ha-1. The corn plots followed soybeans in all years of the study at both locations. 2008 Integrated Crop Management Conference - Iowa State University — 231 Grain N uptake increased with N rate was applied (p>F = <0.0001) in 2003-2005 and 2007 (Table 4). The difference between materials was greatest for ESN treatments in 2005 (p>F = 0.0066) but not significant every other year at KNW (Table 4). In 2004, the ESN treatments had a higher N uptake than the urea treatments. The interaction between material and N rate was not significant in any year of the study. There was also a large amount of variability in grain N uptake in the ESN and urea treatments over the five site-years. Soil conditions, weather, and the coating of the ESN could have influenced N uptake. ra Research and Demonstration Farm (NW) at Sutherland (2003, 2005-2007). The 2004 location at Sutherland received heavy hail damage so no data were collected. The soil types for the experiments at Kanawha and Sutherland are listed in Table 1, while cultural practices are listed in Table 2, and baseline soil data are listed in Table 3. 2005-2007 Soil analysis Soil NH4+-N concentrations were not affected by N rate at the V-6 sample time in any year of the study at KNW. The difference between the two materials was significantly higher for ESN only in 2005 (p>F = 0.0007) (Table 5). The interaction between N rate and material was not significant any year of the study at the V-6 sampling time. In 2006 and 2007, the ESN treatments had higher concentrations of soil NH4+-N. We would not expect the ESN treatments to have higher NH4+-N concentrations at this time because of the release properties of the ESN. Since ESN should be released at a slower rate throughout the season, we would predict that there would be less N available at the V-6 growth stage when compared to the urea treatments. d 230 — 2008 Integrated Crop Management Conference - Iowa State University Soil NH4+-N concentrations at V-15 were increased by the addition of N in 2005 and 2007 (p>F = 0.0017 and 0.0516) (Tables 5, 7). The difference between the two materials was significantly higher for ESN treatments in 2005 and 2007 (p>F = 0.0172 and 0.0224) (Tables 5, 7). The interaction between the two materials was only significant in 2005 (p>F = 0.0194) (Table 6). The average concentrations of soil NH4+-N at this time were higher each year for the ESN treatments compared to the urea treatments. We would expect this to happen because a good portion of the N should still be releasing from the ESN and available for plant uptake. ft Soil NO3--N concentrations at the V-6 sampling time increased with the addition of N every year of the study (p>F = 0.0001, <0.0001, and <0.0001 respectively) (Tables 5, 6, 7). The difference between the two materials was also significantly higher in the urea treatments each year of the study (p>F = 0.0008, <0.0001, and <0.0001) (Tables 5, 6, 7). The interaction between the two materials at the V-6 sampling time was significant in 2006 and 2007 (p>F = 0.0068 and 0.0475) (Tables 6, 7). We expected soil NO3--N concentrations from urea to be higher due to the fact that urea generally hydrolyzes rapidly in soils in the Midwest (Kissel, 1988). Obviously conditions such as temperature, moisture, soil pH and other factors play a role in how fast N from urea becomes plant available. ra At the V-15 sampling time, NO3-N concentrations increased with the addition of fertilizer N every year of the study (p>F = 0.0025, 0.0052, and <0.0001 respectively) (Tables 5, 6, 7). The difference between the two materials was higher for ESN treatments in 2005 (p>F = 0.0001) (Table 5). The interaction between N rate and material was significant in 2005 and 2007 (p>F = 0.0202 and 0.0043) (Tables 5, 7). The average concentrations of soil NO3-N from urea were only slightly higher than soil NO3-N from the ESN treatments in 2006. Generally, this would be expected because N from urea quickly becomes plant available. 2008 Integrated Crop Management Conference - Iowa State University — 233 2005-2007 Soil Analysis Soil NH4+-N concentrations at the V-6 sampling time increased with N rate each year of the study (p>F = <0.0001, 0.0036, and 0.0048 respectively) (Tables 9, 10, 11). Soil NH4+-N concentrations were higher for urea treatments in 2006 and ESN treatments in 2007 (p>F = 0.0345 and <0.0001) (Tables 10, 11). Greater concentrations of NH4+-N from urea would be expected this early in the growing season. When soil samples were collected at the V-15 growth stage, soil NH4+-N concentrations increased with the addition of N during each year of the study (p>F = 0.0093, 0.0054, and <0.0001) (Tables 9, 10, 11). The ESN treatments had higher concentrations of soil NH4+-N each year of the study (p>F = 0.0192, 0.0085, and <0.0001) (Tables 9, 10, 11). Post harvest concentrations of NH4+-N at the 0-30 cm depth were not affected by N rate, but in 2007 ESN treatments had slightly higher soil NH4+-N concentrations (p> F = 0.0759) (Table 11). None of the factors tested in the 31-60 cm depth were affected by N rate or materials. ft Post harvest soil NH4+-N concentrations at the 0-30 cm depth were not affected by any of the factors tested in 2005-2007. Soil NH4+-N concentrations at the post harvest sampling time at the 31-60 cm depth were slightly increased with the addition of N in 2007 (p>F = 0.0636) (Table 7). Soil NO3--N concentrations increased with N rate in every year of the study (p>F = <0.0001, 0.0009, and <0.0001) when taken at the V-6 growth stage (Tables 9, 10, 11). The differences in soil NO3--N concentrations between materials were higher for urea treatments in every year of the study (p>F = <0.0001, 0.0001, and 0.0025) (Tables 9, 10, 11). The interaction between N rate and material was significant at the V-6 sampling time each year of the study (p>F = <0.0001, 0.0434, and 0.0058) (Tables 9, 10, 11). ra 232 — 2008 Integrated Crop Management Conference - Iowa State University Soil NO3--N concentrations increased as N rates increased at the V-15 sampling time every year of the study (p>F = <0.0001, 0.0040, and <0.0001) (Tables 9, 10, 11). Using ESN fertilizer resulted in higher NO3- -N concentrations in 2005 (p>F = 0.0019) (Table 9). In 2006 and 2007, soil NO3-N concentrations were higher in the urea treatments compared to ESN treatments. The interaction between N rate and material was significant in 2005 (p>F = 0.0042) (Table 9). Sutherland location Post harvest soil NO3--N concentrations increased with N rate every year (p>F = <0.0001) (Tables 9, 10, 11). In 2005, there was a trend for ESN treatments to have higher concentrations of soil NO3- -N (p>F = 0.0682) (Figure 4) (Table 9), while ESN treatments had a higher concentration of soil NO3--N than urea treatments (p>F = 0.0003) (Table 11) in 2007. Concentrations of soil NO3- -N at the 31-60 cm depth increased with N rate throughout the study (p>F = <0.0001, 0.0037, and <0.0001) (Tables 9, 10, 11). In 2007, concentrations of NO3- -N were higher in ESN treatments than urea treatments (p>F = <0.0001) (Table 11). The interaction between material and N rate was significant in 2007 (p>F = 0.0286) (Table 11). d Grain production Corn grain yields increased as N rates increased each year of the study (p>F = <0.0001) (Table 8). The difference between the two fertilizer materials was not significant in 2003, 2006, and 2007 but in 2003 (p>F = 0.0885) there was a trend for ESN to yield higher than urea treatments (Figure 3). In 2005, ESN treatments yielded higher than urea treatments (p>F = <0.0001) (Table 8). Corn yields over the four site-years were variable just as at Kanawha. In 2003 and 2006, average corn yields were higher from ESN treatments compared to urea treatments. The higher average ESN yields could be attributed to the coating on the ESN, which can help to prevent loss of N due to leaching out of the soil profile. The interaction between material and N rate was significant in 2005 (p>F = 0.0191) and 2007 (p>F = 0.0214) (Table 8). Grain N uptake increased with the addition of N in 2003 (p>F = <0.0001), 2006 (p>F = 0.001), and 2007 (p>F = <0.0001) (Table 10). Nitrogen uptake was not significant in 2005 (p>F = 0.0761) but there was a trend for ESN to have greater N uptake than the urea treatments (Figure 4). ESN treatments had significantly higher N uptake than urea treatments in 2005 (p>F = 0.0215) (Table 8). In 2003 and 2006, average N uptake from ESN treatments was slightly higher than urea treatments. This could be possibly due to the coating on the ESN. d Post harvest soil NO3--N concentrations at the 0-30 cm depth increased with N rate in 2006 (p>F = <0.0001) (Table 6). No other factors at this depth were affected over the duration of the study. At the 31-60 cm depth, soil NO3--N concentrations increased with the addition of N in 2005 and 2007 (p>F = 0.0007 and 0.0009) (Tables 5, 7). The difference between the two materials was higher for ESN treatments in 2005 (p>F = 0.0014) (Table 5). The interaction between material and N rate was significant in 2005 (p>F = 0.0060) (Table 5). Summary and conclusions The addition of fertilizer N increased corn grain yield at all locations in all years. However, there was a clear statistical advantage for using ESN at only one of the nine site-years. Three of the nine site-years showed a trend in which ESN treatments out-yielded urea treatments. N uptake in corn grain was not generally affected by fertilizer material. Soil NH4+-N concentrations were usually higher for ESN treatments compared to urea at the V-6 and V-15 sampling times. While this was not expected because of the time release properties of the ESN, we can speculate that the ESN was still releasing N while NH4+-N in the urea 234 — 2008 Integrated Crop Management Conference - Iowa State University treatments had probably already converted to nitrate. Post harvest soil samples were generally higher in both nitrate and ammonium from the ESN treatments. It is reasonable to assume that a good portion of this residual N was lost over winter. Lachat Instruments. 1993. QuickChem method 12-107-06-2-A: ammonia (salicylate) in 2 M KCl soil extracts. Lachat Instruments, Milwaukee, WI. Kissel, D.E. 1988. Management of urea fertilizers. North Central Regional Extension Publ. 326. Kansas State University, Manhattan, KS. Trenkel, M.E. 1997. Improving fertilizer use efficiency. Controlled-release stabilized Fertilizers in Agriculture. FAO and IFA, Paris. Pp. 7-27. Wang, F.L., and A.K. Alva. 1996. Leaching of nitrogen from slow-release urea sources in sandy soils. Soil Sci. Soc. Am. J. 60:1454–1458. Corn Grain yield (Mg ha-1) 13 12 11 10 9 ft 8 0 34 67 101 134 168 0 202 7.5 6.0 5.5 5.0 4.5 67 101 134 168 202 Figure 2. Relationship between N rate and corn grain yield at Kanawha, 2005. Figure 1. Relationship between N rate and corn grain yield at Kanawha, 2004. 6.5 34 N Rate (kg ha-1) N rate (kg ha-1) 16 Urea ESN Soil NO3--N concentration (soil ppm) d Lachat Instruments. 1992. QuickChem method 12-107-04-1-B: nitrate (salicylate) in 2 M KCl soil extracts. Lachat Instruments, Milwaukee, WI. 10 ra Hauck, R.D. 1985. Slow-release and bioinhibitor-amended nitrogen fertilizers. p. 294-319. In O.P. Engelstad (ed.) Fertilizer technology and use, 3rd ed. SSSA, Madison, WI. 11 d Gonzalez, M. 2005. Effect of slow release nitrogen fertilizers on corn production in Iowa. Unpublished MS thesis, Iowa State University, Ames, IA. 12 8 Corn Grain Yield (Mg ha-1) ra Allen, S.E. 1984. Slow-release nitrogen fertilizers. p. 195-206. In R.D. Hauck (ed.) Nitrogen in crop production, ASA, CSSA, SSSA, Madison, WI. 13 7.0 Urea ESN 14 9 We believe that this product has the potential to increase corn grain yields in certain situations while preventing N loss (sandy soils, high rainfall locations, etc). Currently the cost of this product and the unpredictability of positive yield responses for ESN make it difficult to recommend ESN to producers as an alternative fertilizer to urea in Iowa. References Urea ESN 14 ft We did not observe any negative yield responses from the use of ESN; however ESN did not consistently result in higher corn grain and biomass yields. The data suggest that slightly higher concentrations of NO3--N and NH4+-N from ESN treatments were left behind in the soil after the corn was harvested. These residual amounts of N could have negative consequences to crop producers due to the fact that nitrate is easily lost from the soil profile if leaching occurs. 15 15 Corn Grain Yield (Mg ha-1) There were large differences among the years and locations in the study when comparing corn grain yield and N uptake in the grain. There could be many reasons for the variability in grain yields such as adverse weather conditions that can favor denitrification and leaching or possibly inhibit the release of N from the ESN granules. Soil conditions throughout the studies could have also been a factor in the inconsistent yields. Conditions that favor N loss could have existed in various years throughout this study. 2008 Integrated Crop Management Conference - Iowa State University — 235 4.0 0 34 67 Urea ESN 14 12 10 8 6 4 101 134 168 202 N Rate (kg ha-1) Figure 3. Relationship between N rate and corn grain yield at Sutherland, 2003. 0 34 67 101 134 168 202 N Rate (kg ha-1) Figure 4. Relationship between N rate and post harvest soil NO3--N concentrations at Sutherland, 2005. 236 — 2008 Integrated Crop Management Conference - Iowa State University 2005 Webster Clarion Fine-loamy, mixed, superactive, mesic Typic Endoaquall Fine-loamy, mixed, superactive, mesic Typic Hapludoll 2006 Nicollet Canisteo Fine-loamy, mixed, superactive, mesic Aquic Hapludoll Fine-loamy, mixed, superactive, calcareous, mesic Typic Endoaquoll 2007 Webster Clarion Fine-loamy, mixed, superactive, mesic Typic Endoaquoll Fine-loamy, mixed, superactive, mesic Typic Hapludoll 2003-2007 Primghar Marcus Fine-silty, mixed, superactive, mesic Aquic Hapludoll Fine-silty, mixed, superactive, mesic Typic Endoaquoll ra Table 2. Cultural practices for all locations and years in the spring-applied ESN/urea studies at Kanawha and Sutherland. Site / Planting Hybrid Population Year date seeds/ha Harvest date 2003 Kanawha Sutherland April 26 May 7 DeKalb 53-32 Bt DeKalb 46-28 74,133 75,368 October 18 October 16 April 28 DeKalb 53-32 Bt 79,040 October 16 April 30 May 4 DeKalb 53-32 Bt FC 7515R 74,100 79,040 October 15 October 19 May 22 May 12 DeKalb 53-32 Bt Pioneer 35Y61 81,510 79,040 October 24 October 24 May 10 May 2 Pioneer 36W69 Kruger 8602 HX 81,510 79,040 October 6 October 11 2004 d Kanawha 2005 Kanawha Sutherland 2006 Kanawha Sutherland 2007 Kanawha Sutherland Kanawha Kanawha Kanawha Kanawha Kanawha Sutherland Sutherland Sutherland Sutherland a organic matter b 1:1 H2O c Bray P-1 d Ammonium Acetate Year OMa 2003 2004 2005 2006 2007 2003 2005 2006 2007 g kg-1 49 61 57 51 53 47 46 46 47 pHb 6.2 5.6 5.8 5.6 5.9 6.3 6.5 6.3 6.3 Pc Kd ----------------mg kg-1--------------21 109 50 191 44 145 34 227 32 255 12 132 11 161 15 168 12 155 ft Fine-loamy, mixed, superactive, mesic Typic Hapludoll Location ra Clarion ft 2004 Table 3. Soil chemical properties at the 0-15 cm depth at Kanawha and Sutherland, 2003-2007. d Table 1. Soil types for all years in the spring-applied ESN/urea studies at Kanawha and Sutherland. Site Year Soil type Soil series description Kanawha 2003 Nicollet Fine-loamy, mixed, superactive, mesic Aquic Hapludoll Canisteo Fine-loamy, mixed, superactive, calcareous, mesic Typic Endoaquoll Sutherland 2008 Integrated Crop Management Conference - Iowa State University — 237 52 74 90 101 102 108 108 91 6.99 9.33 10.57 11.46 10.96 10.98 10.59 10.13 - Urea Average ESN Average NH4 Sample time V-6 V-15 Post Harvest 0-30 cm 31-60 cm -1 --------------------------mg kg------------------------ 0 34 67 101 134 168 202 7.65 7.50 7.35 8.90 7.40 7.50 7.90 7.74 4.00 3.80 3.90 4.15 4.65 4.00 4.20 4.10 0 34 67 101 134 168 202 7.15 8.75 13.25 9.05 15.90 13.25 14.25 11.66 3.90 3.70 4.00 4.20 5.70 6.70 4.45 4.66 4.60 4.25 4.65 4.75 4.70 4.95 4.75 4.66 8.70 9.05 8.20 8.65 9.15 9.05 9.00 8.83 4.70 4.85 4.25 4.45 4.25 4.45 5.00 4.56 -----------------------------p>F--------------------------NS 0.0017 NS NS 0.0007 0.0172 NS NS NS 0.0194 NS NS ra Statistics N rate N material N rate*N material 8.00 9.50 8.50 9.65 8.25 8.50 9.15 8.79 dry weight b -1 155 g kg - NO3 Sample time V-6 V-15 Post Harvest 0-30 cm 31-60 cm -1 -------------------------mg kg------------------------5.50 8.35 18.55 12.45 15.85 21.55 18.25 14.36 1.85 1.75 2.20 2.85 4.25 2.55 2.35 2.54 5.55 5.05 4.85 5.15 5.70 4.95 4.85 5.16 ft -1 a Statistics N rate Material N rate*Material Average N rate kg ha 0 34 67 101 134 168 202 ESN Average Urea + N Material d 84 90 112 117 136 157 151 121 8.83 9.85 11.15 11.41 12.99 13.79 13.41 11.63 89 87 99 117 125 143 146 115 9.32 9.10 10.25 11.23 12.51 12.44 13.37 11.17 0 34 67 101 134 168 202 7.15 8.85 10.85 10.77 11.60 10.98 11.29 10.21 55 72 96 98 107 106 112 92 -1 kg ha -1 Mg ha -1 kg ha + Table 5. Effect of N rate and fertilizer materials on concentrations of soil NH 4 -N and NO3 -N at Kanawha, 2005. ft 85 108 124 126 145 135 128 122 8.44 10.59 11.80 12.62 13.12 12.62 12.69 11.70 9.57 11.48 12.69 14.33 13.57 13.01 13.63 12.61 8.69 10.59 12.62 13.82 13.07 12.80 13.25 12.12 ra 87 100 130 154 136 140 143 127 96 121 136 154 151 151 154 138 9.07 10.91 11.54 11.86 12.69 13.25 13.01 11.76 92 105 128 122 133 141 143 123 -1 kg ha -1 Mg ha -1 kg ha -1 Mg ha -1 kg ha -1 Mg ha d b N uptake 2003 a Yield N Rate N Material 2008 Integrated Crop Management Conference - Iowa State University — 239 ------------------------------------------------------------------------------------p>F----------------------------------------------------------------------------------<0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 NS <0.0001 <0.0001 NS NS 0.0646 NS 0.0671 0.0066 NS NS NS NS NS NS NS NS NS NS NS NS NS NS 58 88 99 114 123 122 128 105 6.24 8.86 10.07 11.20 12.08 11.86 12.08 10.34 6.70 7.88 10.12 10.85 12.11 12.15 12.18 10.28 62 73 104 115 124 134 139 107 -1 -1 Mg ha kg ha a a a Yield b N uptake 2004 a Yield Table 4. Corn grain response to spring applied urea and ESN fertilizers at Kanawha, 2003-2007. N uptake 2005 b Yield N uptake 2006 b Yield N uptake 2007 b 238 — 2008 Integrated Crop Management Conference - Iowa State University 4.95 7.90 9.15 9.25 10.45 15.15 10.50 9.62 1.65 3.90 2.30 3.65 8.95 10.20 11.25 5.99 4.90 5.20 5.30 5.10 6.75 5.75 6.70 5.67 2.05 2.20 2.05 2.40 2.70 2.45 2.35 2.31 1.85 2.35 2.15 2.45 3.35 5.50 5.15 3.26 -----------------------------p>F--------------------------0.0001 0.0025 NS 0.0007 0.0008 0.0001 NS 0.0014 NS 0.0202 NS 0.0060 ESN 0 34 67 101 134 168 202 6.60 8.95 6.85 10.60 10.25 8.00 10.75 8.86 6.35 5.50 6.95 5.80 6.25 6.30 10.90 6.86 7.81 8.61 8.00 8.35 8.96 8.18 8.54 8.35 3.36 3.36 4.39 3.93 4.53 3.78 3.99 3.91 5.95 7.55 8.00 11.25 17.70 13.40 11.65 10.79 3.30 2.90 4.10 5.35 7.35 5.25 10.30 5.51 3.23 3.04 3.56 3.39 3.76 4.54 4.72 3.75 1.24 1.20 1.53 1.41 1.82 2.58 2.65 1.78 Average Statistics N rate N material N rate*N material -----------------------------p>F--------------------------NS 0.0516 NS 0.0636 NS 0.0224 NS NS NS NS NS NS -----------------------------p>F--------------------------<0.0001 <0.0001 NS 0.0009 <0.0001 NS NS NS 0.0475 0.0043 NS NS 56 81 84 99 101 99 116 91 6.21 7.85 8.17 9.88 9.93 9.57 10.66 8.90 60 68 87 105 109 121 123 96 6.37 7.37 8.93 9.99 10.85 10.54 9.76 9.12 a Yield 91 105 103 96 106 114 121 105 93 90 116 131 135 144 160 124 10.21 9.95 11.61 12.93 13.07 13.82 14.97 12.37 108 109 109 119 124 135 123 118 11.03 10.59 11.86 12.43 12.43 13.12 13.69 12.16 107 104 112 123 121 137 140 121 b ft -1 Average 155 g kg dry weight 1.28 1.32 1.21 1.40 1.76 1.38 2.54 1.56 b 3.64 3.50 3.28 3.57 3.34 3.21 4.84 3.63 a 2.25 2.75 3.35 3.95 4.45 11.85 6.90 5.07 9.76 11.48 11.35 10.65 11.48 12.12 11.99 11.26 11.67 11.80 11.42 12.31 12.62 12.62 12.31 12.10 Average 5.90 11.00 17.85 19.70 21.65 24.35 28.20 18.38 38 46 50 58 63 64 65 55 3.99 3.33 3.56 4.25 4.03 3.79 4.27 3.89 4.94 5.77 5.98 6.69 6.98 6.87 6.74 6.28 7.30 7.86 7.96 7.99 8.01 8.09 8.74 7.99 0 34 67 101 134 168 202 4.60 5.60 5.45 4.85 5.25 6.75 6.25 5.54 ESN 6.25 7.45 8.55 7.00 8.50 10.55 9.95 8.32 Average 0 34 67 101 134 168 202 d Urea ra -1 kg ha - NO3 Sample time V-6 V-15 Post Harvest 0-30 cm 31-60 cm -1 -------------------------mg kg------------------------ 38 45 49 53 60 65 68 54 N rate NH4 Sample time V-6 V-15 Post Harvest 0-30cm 31-60 cm -1 -------------------------mg kg------------------------ 4.60 5.55 5.99 6.11 6.87 6.80 6.84 6.11 - 0 34 67 101 134 168 202 + Urea -----------------------------p>F--------------------------<0.0001 0.0052 <0.0001 NS <0.0001 NS NS NS 0.0068 NS NS NS Table 7. Effect of N rate and fertilizer materials on concentrations of soil NH 4 -N and NO3 -N at Kanawha, 2007. N Material N uptake 2007 -1 -1 Mg ha kg ha b 5.75 8.85 3.25 5.45 7.90 9.55 10.05 7.26 -1 + 7.10 6.95 8.65 8.75 10.55 11.75 14.30 9.72 d ra -----------------------------p>F--------------------------NS NS NS NS NS NS NS NS NS NS NS NS 3.05 3.20 6.50 5.40 9.10 8.15 8.35 6.25 kg ha 8.95 9.35 14.35 15.20 12.55 12.95 22.45 13.69 N uptake 2006 -1 -1 Mg ha kg ha 5.30 5.95 2.70 3.50 3.65 3.65 3.75 4.07 a 6.75 7.35 8.00 8.15 7.60 7.40 7.30 7.51 3.10 6.55 5.35 3.90 5.40 5.85 8.15 5.47 Yield 6.70 6.55 7.75 9.10 7.25 8.70 13.75 8.54 b Statistics N rate N material N rate*N material 3.10 4.00 4.25 8.30 6.90 10.30 10.50 6.76 N uptake 2005 -1 -1 Mg ha kg ha 6.35 5.45 7.35 8.70 6.65 7.40 8.35 7.18 9.45 14.20 19.20 24.70 31.95 31.85 29.85 23.03 a 7.60 7.25 11.85 8.85 9.35 8.75 15.85 9.93 3.65 5.00 3.80 2.90 3.00 3.80 3.65 3.69 Yield 0 34 67 101 134 168 202 7.35 7.65 6.95 7.95 8.15 7.80 8.20 7.72 b Average 5.85 5.95 5.65 5.95 6.20 9.10 7.75 6.64 N uptake 2003 -1 -1 Mg ha kg ha ESN 7.10 9.05 8.15 9.55 9.40 8.65 10.25 8.88 2008 Integrated Crop Management Conference - Iowa State University — 241 a Average 0 34 67 101 134 168 202 Yield Urea N rate -1 kg ha Sample time V-15 Post Harvest 0-30cm 31-60 cm -1 -------------------------mg kg-----------------------V-6 Table 8. Corn grain response to spring applied urea and ESN fertilizers at Sutherland, 2003, 2005-2007. N rate - NO3 Sample time V-6 V-15 Post Harvest 0-30 cm 31-60 cm -1 -------------------------mg kg------------------------ ft N Material + NH4 9 -----------------------------------------------------------------------------p>F---------------------------------------------------------------------------<0.0001 <0.0001 <0.0001 0.0761 <0.0001 0.001 <0.0001 <0.0001 0.0885 NS <0.0001 0.0215 NS NS NS NS NS NS 0.0191 NS NS NS 0.0214 0.0619 - Table 6. Effect of N rate and fertilizer materials on concentrations of soil NH 4 -N and NO3 -N at Kanawha, 2006. N Material + Statistics N rate Material N rate*Material 240 — 2008 Integrated Crop Management Conference - Iowa State University 242 — 2008 Integrated Crop Management Conference - Iowa State University + -1 kg ha Urea Average ESN 6.20 7.00 7.50 10.85 10.90 13.15 23.80 11.34 10.45 11.25 11.40 12.90 12.45 13.60 10.80 11.84 0 34 67 101 134 168 202 6.35 7.80 9.50 9.50 7.35 8.90 16.15 9.36 10.45 10.90 12.70 11.85 14.80 20.50 17.40 14.09 6.05 6.00 6.45 6.10 5.85 6.10 6.75 6.19 10.95 10.05 10.25 10.75 10.55 10.65 10.20 10.49 5.65 6.25 5.90 5.90 6.40 6.30 6.05 6.06 -----------------------------p>F--------------------------<0.0001 0.0093 NS NS NS 0.0192 NS NS NS NS NS NS d ra Statistics N rate N material N rate*N material 10.40 10.35 11.10 10.90 10.80 10.70 11.05 10.76 10.85 11.25 15.35 18.70 14.20 23.45 31.00 17.83 3.40 3.35 5.35 4.65 10.15 24.90 22.35 10.59 4.95 4.85 4.95 5.40 5.30 9.95 9.45 6.41 13.35 11.70 12.20 13.85 11.25 13.80 14.90 13.01 3.90 4.55 7.80 11.35 16.50 20.65 41.40 15.16 4.85 5.30 5.80 7.20 6.60 10.90 15.45 8.01 -1 kg ha 3.25 3.20 3.50 3.50 4.20 8.90 12.90 5.64 Urea 3.05 3.55 4.15 5.10 5.70 9.05 10.35 5.85 ESN -----------------------------p>F--------------------------<0.0001 <0.0001 <0.0001 <0.0001 <0.0001 0.0019 0.0682 NS <0.0001 0.0042 NS NS N rate Average Average Sample time V-15 Post Harvest 0-30cm 31-60 cm -1 -------------------------mg kg-----------------------V-6 0 34 67 101 134 168 202 6.80 8.95 8.70 10.10 21.55 14.20 13.70 12.00 7.40 6.35 6.45 7.35 7.20 7.05 7.95 7.11 9.40 9.55 9.25 9.65 9.45 8.55 9.70 9.36 4.60 5.90 6.60 5.55 6.05 5.15 5.90 5.68 8.50 11.15 11.90 11.60 22.50 15.65 18.90 14.31 4.50 5.15 5.90 9.95 12.00 10.90 12.75 8.74 5.85 9.10 6.45 8.35 10.85 15.00 19.55 10.74 2.90 3.75 4.80 5.35 6.50 6.75 9.70 5.68 0 34 67 101 134 168 202 6.80 7.35 9.20 11.55 9.40 11.90 10.15 9.48 6.20 6.75 8.35 8.70 9.10 7.80 13.50 8.63 9.75 8.50 8.45 9.50 10.60 9.90 11.10 9.69 5.25 5.70 4.95 5.85 5.50 6.40 7.50 5.88 7.35 7.40 10.15 10.85 9.25 9.95 12.95 9.70 3.30 5.45 5.50 7.90 7.60 9.55 10.60 7.13 5.65 7.40 8.80 12.50 14.20 20.75 19.10 12.63 3.35 4.30 3.20 5.15 4.65 9.85 12.35 6.12 10 Average 0 34 67 101 134 168 202 N Material - NO3 Sample time V-6 V-15 Post Harvest 0-30 cm 31-60 cm -1 -------------------------mg kg------------------------ Statistics N rate N material N rate*N material ft N rate - NO3 Sample time V-6 V-15 Post Harvest 0-30 cm 31-60 cm -1 -------------------------mg kg------------------------ ft N Material + NH4 -----------------------------p>F--------------------------0.0036 0.0054 NS NS 0.0345 0.0085 NS NS NS 0.0772 NS NS ra + NH4 Sample time V-6 V-15 Post Harvest 0-30cm 31-60 cm -1 -------------------------mg kg------------------------ - Table 10. Effect of N rate and fertilizer materials on concentrations of soil NH 4 -N and NO3 -N at Sutherland, 2006. - Table 9. Effect of N rate and fertilizer materials on concentrations of soil NH4 -N and NO3 -N at Sutherland, 2005. d + 2008 Integrated Crop Management Conference - Iowa State University — 243 -----------------------------p>F--------------------------0.0009 0.0040 <0.0001 0.0037 0.0001 NS NS NS 0.0434 NS NS NS + N rate -1 kg ha Urea Average ESN 8.35 8.65 8.90 9.45 8.95 9.35 11.35 9.29 9.30 9.00 9.65 10.10 9.85 10.10 11.95 9.99 0 34 67 101 134 168 202 9.90 11.00 12.10 11.70 13.65 9.95 15.75 12.01 9.10 10.20 11.45 11.45 11.20 12.40 15.05 11.55 5.05 4.53 4.93 4.56 4.90 4.90 5.36 4.89 9.31 9.93 9.78 9.20 9.75 10.95 10.20 9.87 5.12 4.59 4.87 5.24 4.78 5.21 4.72 4.93 -----------------------------p>F--------------------------0.0048 <0.0001 0.0759 NS <0.0001 <0.0001 NS NS NS NS NS NS d ra Statistics N rate N material N rate*N material 9.40 9.26 10.10 9.13 10.21 9.45 10.90 9.78 7.00 10.70 16.05 22.55 21.50 23.80 38.35 19.99 3.40 4.80 6.40 14.10 16.95 12.80 25.60 12.01 6.75 12.05 13.75 19.05 23.75 15.75 26.80 16.84 3.00 5.55 7.45 11.90 9.90 13.95 18.60 10.05 3.75 3.47 3.50 4.23 4.04 5.67 6.53 4.46 1.73 1.94 2.13 2.14 2.87 2.90 5.19 2.70 3.42 4.40 4.46 4.33 7.76 8.39 7.61 5.77 2.03 2.37 2.30 3.18 5.53 6.11 6.44 3.99 -----------------------------p>F--------------------------<0.0001 <0.0001 <0.0001 <0.0001 0.0025 NS 0.0003 <0.0001 0.0058 NS 0.0316 0.0286 Fertilizing crops in the new price age – nitrogen John E. Sawyer, Professor, Agronomy, Iowa State University Introduction Fertilizers have been at unbelievably high prices, with tight supplies for some fertilizers. Total crop production costs are causing credit supply issues, which complicates decisions to allocate available funds for production expenses. Crop prices are changing rapidly, as are fertilizer prices. High corn and soybean prices certain help pay for expensive fertilizer and provide even greater net return to fertilization. However, the recent reduction in crop prices makes payoff of fertilizer and other production costs more problematic, and uncertain prices makes planning for next year difficult. On top of these monetary issues, mother nature has given us wet conditions in 2008 causing many issues related to nitrogen (N) management, timeliness of field operations, and quite variable crop yields. These issues combined are causing producers to consider changing production practices, including cutting back on fertilizer use. There is no simple answer, and sometimes no change is the correct approach. 12 Average 0 34 67 101 134 168 202 - NO3 Sample time V-6 V-15 Post Harvest 0-30 cm 31-60 cm -1 -------------------------mg kg------------------------ ft N Material NH4 Sample time V-6 V-15 Post Harvest 0-30cm 31-60 cm -1 -------------------------mg kg------------------------ Nitrogen rate decisions Nitrogen applications should be tailored for the crop rotation. As we’ve know for a long time, corn following different previous crops requires adjustment in N application rates. Figure 1 shows this for a recent four-year period of corn yield response to N rates in a long-term rotation study conducted at the Northeast Research Farm at Nashua, IA. First-year corn following well established alfalfa often needs no N fertilization, and when required only 30-40 lb N/acre. Corn following soybean or second-year corn after alfalfa has similar N application requirement, and less than corn following corn. Corn, either continuous, second-year, or third-year has similar response to N rate and the highest fertilization rate need. ra - Table 11. Effect of N rate and fertilizer materials on concentrations of soil NH 4 -N and NO3 -N at Sutherland, 2007. 2008 Integrated Crop Management Conference - Iowa State University — 245 Unfortunately, corn almost always needs N fertilization (other than corn following well established alfalfa), and yield increase with N application is quite good (Figures 1 and 2). Therefore, there are not many opportunities to eliminate application when N prices are extraordinarily high or in short supply. Nitrogen can be supplied from manure, but that is also a valuable commodity and the amount of manure produced in Iowa cannot meet the needs of all corn production. If N fertilizer is in short supply or purchases have to be limited, it is better to apply some N to all fields than to skip fields (other than corn after alfalfa) as the largest yield gains come from the first increments of applied N (Figure 2). d + ft 244 — 2008 Integrated Crop Management Conference - Iowa State University Application rates can be adjusted downward when N fertilizer costs are high relative to corn prices. However, closely observe both N and corn prices before deciding on reducing N applications. Despite the high N prices, corn prices in 2008 were also high and therefore the ratio between the two had not changed dramatically. For 2009, that relationship could be different if corn prices continue lower and N prices remain high. The Corn Nitrogen Rate Calculator (http://extension.agron.iastate.edu/soilfertility/nrate.aspx) was updated this summer with Iowa data from N rate trials conducted in 2007. Based on that dataset, the suggested N rates and rate ranges for four N:corn price ratios are listed in Table 1 and shown in Figure 3. The advantage of the calculator is that specific N and corn prices can be compared. For example, ra Grow more corn after soybean d If possible, grow more corn after soybean than after corn. Yields will typically be higher with the rotation and N application need lower (Figures 1 and 2). Compared to continuous corn, corn in rotation with soybean has lower N requirement, ranging from 45 to 60 lb N/acre less (Figure 2). And, the average corn yield is 14% lower for continuous corn compared to corn following soybean (Figure 2). For three of the sites in the N rate by rotation study included in Figure 2 that have been harvested as of the writing of this report, continuous corn yields range from 20 to 30% lower. Yield in continuous corn is not always lower than rotated corn, but the frequency of that occurrence is low. Out of the 46 site-years of data from 2000-2007 included in Figure 2, five times continuous corn has had higher yield than corn following soybean (2 to 12 bu/acre range), and only two times has yield for continuous corn been only 0 to 5 bu/acre less than yield of corn following soybean. This means that 39 times (85% of the time) corn rotated after soybean has had more than 5 bu/acre higher yield than continuous corn (5 to 76 bu/acre range, average of 29 bu/acre). In addition, the standard deviation in yield across years and sites is lower for corn grown after soybean than continuous corn (42 bu/acre for rotated corn and 51 bu/acre for continuous corn), indicating less production variation with rotated corn. Dealing with uncertainty Decisions as to what N rate to apply in a specific corn production year are influenced by many factors. Important ones, such as rotation and N/crop prices, are discussed above. Other decisions attempt to deal with known, but unpredictable factors influenced by weather such as soil N processing (net mineralization), nitrate losses (denitrification and leaching), and crop N demand. Management of potential losses typically focuses on time of application to minimize nitrate buildup in soil during the springtime and early summer when the potential for loss is greatest. Even application timing and practices used to reduce rate of nitrate formation (such as inhibitors) have limited length of effectiveness which eventually results in nitrate buildup that is then subject to losses (such as an inhibitor loses ability to slow nitrification, wet soils occur mid- to late in the growing season, etc.). In addition, nitrate formed by soil mineralization cannot be controlled, hence the N loss from soil derived nitrate cannot be controlled either. This means that in wet years, corn N response (i.e. the N rate to optimize yield response) will be greater even if loss of applied fertilizer N is perfectly controlled. In addition, soil temperature and moisture directly influence soil N mineralization, which therefore increases/decreases in warmer-wetter years and drier-cooler years. These soil processing factors drive much of the variation in optimal N rates found between years. Additional variation occurs due to loss of applied N. An example of the yearly variation in optimal N rate and corn yield is shown in Figure 4 for a site at Ames on a Clarion loam soil. That variation is typical. There are many other examples. For instance, small plot N rate trials (in an area of approximately 0.4 acre) conducted in exactly the same location in two producer fields in 2001 and 2003 (corn rotated with soybean, soybean in 2002) resulted in differences in economic optimum N rates between years of 33 and 44 lb N/acre at the respective sites. ft ft The output from the calculator gives suggested N rate ranges that provide similar profitable return. With high N costs and perhaps the need to allocate limited funds for N fertilizer purchase, one can consider using rates in the lower part of the suggested ranges. Those rates should provide similar yields, but risk of N supply shortage to the crop is greater if N losses occur or if corn is more N responsive than typically found. The rates suggested from the Corn Nitrogen Rate Calculator are the same whether N is applied in late fall, spring, or sidedress; therefore, do not decrease the rate for sidedress application timing. Fall and early spring application carries more risk of loss, however, that risk cannot be predicted and it is not appropriate to guess and just increase the rate in an attempt to cover potential losses. When N is expensive, applications above the MRTN rate result in large economic losses. This can be seen in graphs produced from the Corn Nitrogen Rate Calculator (Figure 3). Therefore, high rates are not an economical approach to ensure high yield. 2008 Integrated Crop Management Conference - Iowa State University — 247 Yearly variation in N response and yield is really quite normal, with influences as discussed above. The question that arises is how much does this variation “cost” in terms of yield or economic loss if something other than the optimal rate is applied each year, or even more pertinent, what does this type of variation mean when using MRTN rate recommendations as produced by the Corn Nitrogen Rate Calculator? To answer these questions, the N response trial database used in the calculator was queried to determine the economic net return increase potential from use of each site-year economic optimum N rate (0.10 price ratio) compared with using the MRTN rate across all sites. For corn following soybean the average increase was $12/ acre and for continuous corn was $19/acre, neither an exceptionally large amount. Those values include both unneeded fertilizer cost with over-applications and yield loss cost with underapplications. The influence of the MRTN rate on percent of maximum yield across economic optimum N rates is shown in Figure 5 for trial sites with corn following soybean. Clearly the MRTN rate is protective of yield, with yield decline of any substance only for a very few trial sites (14 out of 165 sites) with very high economic optimum rates (for example, sites with additional response due to N losses). Response trial datasets, like in the Corn Nitrogen Rate Calculator, are used to help “predict” (recommend) N application need for an unknown future. That approach does provide a reasonable level of confidence for achieving a corn crop’s yield potential, within bounds of maximizing but not perfecting economic return to N. ra with N at $0.43/lb N (anhydrous ammonia at $705/ton) and corn at $4.78/bu, the ratio is 0.09 and the Maximum Return to N (MRTN) rate is 133 lb N/acre for corn following soybean (range 120-146 lb N/acre); with N at 0.73/lb N (ammonia at $1200/ton) and corn at $3.50/bu, the ratio is 0.21 and the MRTN rate is 98 lb N/acre (range 88-110 lb N/acre). d 246 — 2008 Integrated Crop Management Conference - Iowa State University In addition, N rate guidelines cannot be set at a rate to meet the response of all sites. That approach may protect yield for all fields, but is uneconomical and costly to attempt for the majority. That can be seen by looking at economic return results in Figures 3 and 6. Nitrogen rate recommendations are a balancing act between over- and under-application potential. Analysis of large N rate response trial datasets help to not only determine best economic application rates, but also give insight into potential economic consequences for use of suggested rates. Figure 6 shows that the minimization of under- and over-application occurs at the MRTN rate (and within the range of profitable rates). The MRTN rate is not perfect as the point where the two return lines cross is slightly below zero net return ($12/acre). However, that point is not very far below zero (perfection), and thus indicates the “field-to-field” potential return improvement to N rate selection is quite small. Figures 3 and 6 also show that economic risk is much greater for under-application than over-application. At higher N prices relative to corn prices those risks become more similar (Figure 3). 248 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 249 on application rates. The relationship between N and corn prices may or may not have resulted in a need for reducing N applications or using significantly different rates. Also of importance is to manage N inputs in ways to help ensure good efficiency and high crop yield. High fertilizer prices have many producers considering options that may or may not make sense or work well, including blanket reduction in rate or significant change in management such as time of application, fertilizer material, or additive. In many instances, producers are already using good N management practices, and therefore should simply continue as before. For others, there may be room for improvement. Decisions need to be made by producers with concurrent planning with advisers and input providers so new systems can be implemented successfully. Significant N loss situations, like in many areas of Iowa this year, cannot effectively be managed by rate selection (recommendation systems) because occurrence and magnitude of those events is an unknown. Instead, if excessively wet conditions occur, use of tools like estimation of nitrate losses, in-season crop canopy N stress sensing, and soil nitrate testing can be implemented for guidance on supplemental N applications. These tools may not necessarily determine specific application rates, but can help determine if there is adequate N or if additional application is needed. Another approach is just waiting to see what the spring rainfall situation is and using split/sidedress for some N applications, especially when prices are high. As discussed above, attempting to manage potential losses through selection of high application rates is not profitable for long-term N management. Various N management information is available on the ISU Agronomy Extension Soil Fertility Web site at http://www.agronext.iastate.edu/soilfertility/homepage.html. The Corn Nitrogen Rate Calculator is located at http://extension.agron.iastate.edu/soilfertility/nrate.aspx. The rationale behind the Corn Nitrogen Rate Calculator and other information about corn N fertilization is contained in the publication Concepts and Rationale for Regional Nitrogen Rate Guidelines for Corn located at http://www.extension.iastate.edu/Publications/PM2015.pdf. Working with clientele Dealers and crop advisers should work closely with their producer clientele to determine the best options and production plans for the upcoming year, and beyond. This is always important, but more so at this time as the fertilizer purchase/supply/price dynamics are changing dramatically and quickly. Decisions made now, when multiplied across the combined crop production acres in Iowa, can have serious and far reaching effects for the 2009 cropping year. Summary Nitrogen management for corn production has always been challenging. With current and rapidly changing N fertilizer and corn prices it has become even more challenging, with increased uncertainty and risk. Of main importance is to closely consider prices when deciding ft ra 200 C-c-a-a 175 c-C-a-a C-c-c-s C-c-s C-s 150 125 100 d d With high costs for N fertilizers, and especially if wet springs continue, careful management of N fertilizer inputs will be more important than ever to help deal with weather induced N loss uncertainty. Also, products designed to enhance effectiveness of N fertilizers (such as urease inhibitors, nitrification inhibitors, controlled release products) are now relatively less expensive with high fertilizer costs. This means that more options are more viable (especially compared to the practice of simply applying a higher N rate) to help provide for good efficiency of applied N and reduce N loss variability. The same holds for following best application timing and method for N fertilizer products. Reference material Corn Grain Yield (bu/acre) ra ft Why does a fairly wide range in site-year economic optimum N rate result in such small differences in yield and economic net return to N application when a constant (recommended) N rate is used at all sites? The main reason is that the yield response curve for individual sites most often has a shape like that in Figure 2, that is, the yield change is very small at rates just below and above the economic optimum and that economic optimum rates are near the maximum corn yield response (near the “flat” part of response curves). This means that N rates can vary around the economic rate but the yield does not change much. Yield has a large impact on net economic return, therefore, net return tends to be stable. This result is why the profitable range of N rates provided by the Corn Nitrogen Rate Calculator (Table 1) is within $1.00 of the MRTN rate and that those N rate ranges are fairly wide. As N costs do get more expensive relative to corn price (larger price ratios), the net return curve is more “peaked” and the ranges narrow (Figure 3). This means that N rate decisions and N supply to corn are more critical than with lower price ratios. 75 cont C c-C-s c-C-c-s c-c-C-s 50 25 Mallarino, Ortiz-Torres, Pecinovsky, ISU 0 80 160 N Fertilizer Rate (lb N/acre) 240 Figure 1. Corn grain yield response to fertilizer N application rate with various corn rotation sequences at Nashua, IA. A.P. Mallarino and K. Pecinovsky, Iowa State University Northeast Research and Demonstration Farm 2006 annual progress report ISRF06-13. 0 40 80 120 160 Nitrogen Rate, lb N/acre 200 240 d ra Figure 2. Comparison of corn grain yield response to N fertilizer rate and economic optimum N rate (EONR) at a 0.10 price ratio for corn following soybean (SC) and continuous corn (CC) across seven sites in Iowa from 2000-2007, J. Sawyer and D. Barker. Figure 3. Effect of N:corn grain price ratio on return to N with corn following soybean, based on the current Corn Nitrogen Rate Calculator dataset. The solid symbols are the maximum return to N (MRTN) and the light symbols represent the range of similar profitability. 150 100 100 50 50 0 0 Year Figure 4. Yearly variation in economic optimum N rate (bars) (0.10 price ratio) and yield at the optimum N rate (symbols) for corn following soybean (SC) and continuous corn (CC) for a site at Ames, J. Sawyer and D. Barker. 30 20 10 Frequency Percent Maximum Yield 100 80 60 40 20 0 d 0 % of Sites 20 150 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 CC 14 % Lower Yield CC 44 lb N/acre Greater N Need 200 ft 40 200 0-25 2550 % Maximum Yield CC 60 250 ra 80 SC Yield at EONR: 175 bu/acre SC EONR: 134 lb N/acre CC Yield at EONR: 150 bu/acre CC EONR: 178 lb N/acre 250 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 N Rate, lb N/acre 120 ft Corn Yield, bu/acre SC 100 CC SC 180 140 Economic N Rate Yield at Economic N Ames Seven N Rate by Crop Rotation Sites (46 Site-Years) 2000-2007 SC and CC Rotations 160 2008 Integrated Crop Management Conference - Iowa State University — 251 Yield, bu/acre 250 — 2008 Integrated Crop Management Conference - Iowa State University 0 50- 75- 100- 125- 150- 175- 200- 22575 100 125 150 175 200 225 250 EONR, lb N/acre Figure 5. Site-year N rate trial economic optimum N rate frequency (bars) (0.10 price ratio) and percent of maximum yield (symbols) provided if the MRTN rate (128 lb N/acre) is applied at all sites, corn following soybean dataset for Iowa in the Corn Nitrogen Rate Calculator. 252 — 2008 Integrated Crop Management Conference - Iowa State University 50 Antonio P. Mallarino, Professor, Agronomy, Iowa State University 0 100 150 200 250 What is the problem? -100 Site Frequency of EONR's >N Rate Net Loss for Sites with EONR's >N Rate Site Frequency of EONR's <N Rate Net Loss for Sites with EONR's <N Rate ft -150 -200 Applied N Rate, lb N/acre Figure 6. Net return for different N rates applied across the corn following soybean N rate trial database in the Corn Nitrogen Rate Calculator and frequency of sites that have site-year economic optimum N rates (0.10 price ratio) above or below each N application rate. ra Table 1. Nitrogen rates suggested for corn following soybean and continuous corn based on the current Corn Nitrogen Rate Calculator dataset. Nitrogen rate guidelines in Iowa for different N and corn grain prices. Price Ratio1 $/lb:$/bu Corn Following Soybean Rate2 Range3 Corn Following Corn Rate2 Range3 - - - - - - - - - - - - - - - - - lb N/acre - - - - - - - - - - - - - - - - 150 136 - 166 208 194 - 238 0.10 128 116 - 142 183 171 - 199 0.15 113 102 - 124 163 151 - 177 0.20 100 91 - 111 147 137 - 158 d 0.05 1 Price per lb N divided by the expected corn price. For this table, corn was held at $4.50/bu and N varied from $0.23, $0.45, $0.68 to $0.90/lb N (for example, anhydrous ammonia at $377, $738, $1115, to $1476/ton). 2 Rate is the lb N/acre that provides the Maximum Return To N (MRTN). All rates are based on results from the Corn N Rate Calculator as of July 1, 2008 (http://extension.agron.iastate.edu/soilfertility/nrate.aspx). Range is the range of profitable N rates that provides a similar economic return to N (within $1.00/acre of the MRTN). Profitable crop production requires appropriate soil phosphorus (P) and potassium (K) levels, so careful fertilization planning is required. Grain and fertilizer prices have increased significantly during the last two years. Increasing prices may not be a major issue as long as the historical ratio between crop and fertilizer prices is approximately maintained. Recently, however, fertilizer prices have been increasing steadily while grain prices have fluctuated significantly. If there is a crop yield response to fertilization, high crop prices certainly help pay for more expensive fertilizer and may result in even greater net return to fertilization than when crop prices are low. The problem is that largely unpredictable price fluctuations complicate fertilization decisions and encourage many producers to change production practices and cut fertilizer rates. Reducing P and K rates across all conditions is not necessarily a good management decision, however. Test soils for P and K levels ft 50 Soil testing is the most important diagnostic tool on which P and K fertilization should be based. Compared to the cost of nutrient inputs, soil testing has become less expensive, provides an objective basis for making P and K fertilization decisions, and investment in soil sampling and testing results in good returns. Soil testing is not a perfect tool but is very useful and should be used to know what fertilizer rates are needed. Soil-test levels vary greatly across and within Iowa fields. Field research conducted over the years has been used to develop Iowa soil sampling and soil-test interpretations for P, K, and lime. See the ISU Extension publication PM-287, Take a Good Sample to Help Make Good Decisions, for soil sampling suggestions. Research has shown that dense soil sampling methods (such as grid sampling) and frequent soil sampling (every 2 years instead of every 4 years for corn-soybean rotations, for example) coupled with variablerate fertilizer application result in better nutrient management. These practices are more costly than sampling by soil type every 4 years, for example, but their profitability increases with high fertilizer and grain prices. ra 0 -50 d $/acre or % Frequency 2008 Integrated Crop Management Conference - Iowa State University — 253 Fertilizing crops in the new price age – Phosphorus and potassium 100 3 For soil-test interpretations and fertilizer recommendations see ISU Extension publication PM 1688, A General Guide for Crop Nutrient and Limestone Recommendations in Iowa. Table 1 shows a summarized version of the tables with recommendations for corn and soybean grain harvest. Field research has shown that the percentage of P and K applications expected on average to produce a yield response within each soil-test category is 80% for Very Low, 65% for Low, 25% for Optimum, 5% for High, and < 1% for Very High. This means that as soil-test levels increase, the probability of a yield increase to fertilization and the size of expected yield increase decrease. Philosophies about soil-test interpretations and fertilizer recommendations vary across states and countries. Some emphasize short-term profitability from fertilization, a high return per pound of fertilizer applied, and reduced risk of fertilizer over-application What soil-test levels should be maintained? d Allowing a soil-test decline in soils testing in the Optimum soil-test category may result in a yield loss. Application of P and K based on crop removal are recommended for the Optimum soil-test class as publication Pm-1688 indicates, and the provided default rates should be adjusted for actual yield levels. After fertilizer or manure application, the most important factor determining change in soil-test P and K values over time in Iowa soils, is P and K removal with harvest. Due to crop removal, however, withholding fertilizer or manure P and K applications will result in a gradual soil-test decline (see example for P in Fig. 2). Allowing a soil-test decline to occur in high-testing soils increases the profitability of crop production because there is a very low probability of yield response to fertilization, and in the case of P also reduces the risk of water quality impairment. Some believe that allowing a soil-test K decline may not be a good business decision because a K excess has no environmental impact and K fertilizer prices may be even higher in the future. This would be considered a risky business decision that each producer should ponder carefully, and may not be a good nutrient management decision. Although both P and K can be “banked” in Iowa soils, the rate of soil-test decline becomes greater as the soil-test level increases, probably due to larger nutrient loss with soil erosion, surface runoff, and “luxury” uptake and removal especially with corn silage and hay. Research has shown the large effect of yield level on P and K removal and the fertilization rate needed to maintain soil-test values. This is a very important concept to remember, especially because of increasing corn and soybean yields. Although maintaining soil-test values in the Optimum category is a good practice to sustain profitable crop production over time, fertilizer applications can be reduced or even withheld until the next year. This is because the removalbased rate is designed to maintain soil-test values, the probability of a yield response in this test category is 25% or less, and the expected yield response is small. Applying a rate lower than the removal-based rate may be reasonable when the fertilizer/grain price ratio is higher than usual, fertilizer or manure supply is scarce, limited funds are needed for more critical production inputs, or land tenure is uncertain. And, any profit increase will be temporary because higher application rates will be needed in the future. Soil-test decline without sufficient P and K application is gradual but does occur (Fig. 2). Therefore, application of partial crop removal or commonly used starter rates will provide adequate fertilization for the small and occasional yield response in the Optimum category for one year but will not avoid a soil-test decline over time. ft ra No matter the philosophy supporting recommendations, however, the net returns to investment in fertilizer are high in low-testing soils, decrease as soil-test levels increase, and usually become negative at the High and Very High test categories (see an example for P in Fig. 1). Fertilization of low-testing soils usually results in significant returns even with current high P and K fertilizer prices because the probability of a large yield response is high. In high-testing soils, however, the likelihood of large loss to investment in fertilization is very high with current prices because the probability of a yield response is very low and any response is small. Therefore, avoiding unnecessary fertilization of high-testing soils is the most profitable change a producer can use in times of high or uncertain prices. Based on expected yield increases, the Optimum soil test category in Iowa is the most profitable category to maintain over time, with application of removal-based rates. However, decisions are not simple and there is no single best answer concerning fertilization of soils testing in the Optimum category when prices fluctuate significantly. 2008 Integrated Crop Management Conference - Iowa State University — 255 Many producers apply once before corn the P and K needs of corn and soybean. Previous and ongoing long-term research shows that this practice is as effective as applying those nutrients ahead of each crop, but only as long as the fertilizer applied is sufficient for both crops. If fertilizer price or supply will be better next fall (which is difficult to predict), money could be saved now by applying the nutrient need of one crop and fertilizing again next year. The cost of fertilizer application in relation to total fertilizer or crop production costs is relatively less than in the past. Therefore, making single-year applications when fertilizer prices are temporarily high is a reasonable option. ra ft by accepting moderate risk of yield loss (often referred to as sufficiency philosophy). Others emphasize long-term profitability from fertilization, maximum returns over a long term, and reduced risk of yield loss due to insufficient fertility (often referred to as buildup and maintenance philosophy). The philosophy behind soil-test interpretations in Iowa (as in most Midwestern states) combines aspects of both philosophies. Based on expected yield increases and returns, fertilizer applications for low-testing Iowa soils are designed to be profitable, to minimize risk of yield loss, and to increase soil-test values to the Optimum category over time. Moderate soil-test buildup happens even with economically optimum rates, and is explained by partial plant uptake, recycling to the soil with residues, and soil properties that keep P and K in crop-available forms over time. Most Iowa soils have no chemical and mineralogical properties that result in significant transformation of applied P and K into unavailable forms as can happen in soils of other regions. Therefore, much of the applied P and K to Iowa soils can be “banked” in the soil. Can fertilizer rates for low-testing soils be reduced with high prices? A short answer is yes but only by accepting a high risk of yield and profit loss, and doing so when funds are insufficient to buy other critical inputs and/or with very uncertain land tenure. Reasons for this short answer should be obvious after the discussion in the previous sections. Reducing the fertilizer rate in low-testing soils seldom is a good business decision because there is a high probability of a large crop response to fertilization and profit, and recommended rates slowly build up soil-test values to levels that should be maintained for long term productivity and high economic return. Some producers speculate that similar yield levels can be achieved by using reduced planterband P and K fertilizer rates compared with broadcast fertilization in low-testing soils. Iowa research across many years on many fields indicates that this is not the case. Less than optimum fertilizer rates, no matter the placement method, reduce total return to fertilization, but do increase the return per pound of nutrient applied. This is because of the usual curvilinear shape of the crop response to fertilization. The yield increase per pound of nutrient applied is largest at very low rates and decreases as the rate increases, and so do returns per pound. Because P or K rates higher than optimal rates seldom decrease yield, a yield plateau is reached at a certain rate. A maximum total return is achieved at a rate lower than the rate that maximizes yield (how lower depends on price ratios) and higher rates decrease total return, which may become negative with excessively high rates. Figure 3 shows an example of grain yield and returns from K fertilization for two field trials in soils with different soil-test K. Therefore, producers should carefully study if and when application rates to low-testing soils can be reduced, and a sound decision requires consideration of many factors including the producer business management philosophy. d 254 — 2008 Integrated Crop Management Conference - Iowa State University 256 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 257 What about substituting expensive fertilizer with manure P and K? References Manure can supply many nutrients required by crops, including nitrogen (N), P, and K and is a resource that can always be used but especially when fertilizer prices are very high. Because manure contains many nutrients, applications should consider not only what is needed for the crop to be grown but also the ratio of nutrients as determined by manure analysis. The many issues that should be considered when using manure to supply P and K for crops, which include availability of manure nutrients and management practices, will not be addressed here because a very recent ISU Extension publication discusses those issues and provides research-based application guidelines (see PR 1003, Using Manure Nutrients for Crop Production). As this publication indicates, manure K (all inorganic) is 90 to 100% available for crops and manure P (both organic and inorganic in variable proportions) is 90 to 100% available in swine and poultry manures but 60 to 100% available in beef and dairy manures. These availability ranges account for variation in manure sampling and analysis and also for the importance of adequate P and K supply with deficient to adequate soil-test levels. Mainly with beef and dairy manure, a portion of manure P may not be available immediately after application but all P is potentially available over time. The lower availability values are recommended for low-testing soils where large yield loss could occur if insufficient P or K is applied and a reasonable buildup is desirable. The highest availability values should be used when manure is applied to maintain soil-test P and K in the Optimum soil test category, when a removal rate is recommended and the probability of a yield response is low. Manure is an excellent source of P and K for crops when used based on appropriate manure testing and with careful application methods, and is a good way of using available resources especially when fertilizer prices are high or supply is scarce. Extension publications referred to in this article are available ISU Extension Publications web page (http://www.extension.iastate.edu/Publications) and the Agronomy Extension Soil Fertility web site (http://www.agronext.iastate.edu/soilfertility/homepage.html). Table 1. Soil-test interpretations for P and K and fertilization rates for corn and soybean from publication Pm-1688.† Corn Yield ‡ 150 bu 0-8 Low 9-15 Optimum 16-20 High 21-30 Very low 0-90 Low 91-130 Optimum 131-170 High 171-200 50 bu 60 bu --------------- lb P2O5 or K2O/acre --------------100 100 80 80 75 75 60 60 55 75 40 48 0 0 0 130 130 120 120 90 90 90 90 45 60 75 90 0 0 0 0 ra K Very low 200 bu ft P † Interpretations for soil series with low subsoil P and K and for K fine-textured soil. ‡ See publication Pm-1688 for guidelines to adjust maintenance rates for the Optimum category. § Bray-1 or Mehlich-3 tests with a colorimetric determination for P and ammonium acetate or Mehlich-3 for K. 125 CORN SOYBEAN CORN SOYBEAN 100 $4.50/bu corn $12.0/bu soyb $0.60/lb P2O5 Historical Prices 75 d RETURNS TO 46 lb P2O5 ($/acre) d Soil testing and estimates of P and K removal are key pieces of information that should be used together with fertilizer/crop price ratios when deciding P and K application rates. Although many nutrient management considerations in relation to prices are similar for all nutrients, there are some clear differences for P and K compared with N. One main difference is that soiltest P and K levels of Iowa soils can be managed for buildup, maintenance, or draw-down over time. An important consequence is that although a higher than optimum N rate almost always means an investment loss for the excess N portion, an excessive P and K rate one year does not necessarily means money lost. Most of the P and K applied in excess will be available for the following crop, and soil testing can be used to adjust future application rates. Rapidly changing fertilizer and crop prices, however, make P and K management more challenging than in the past. Producers, crop consultants, and dealers should consider factors other than fertilizer/crop price ratios such as fertilizer and manure supply, producers’ economic conditions in relation to purchase of critical production inputs, land tenure, and producers’ business management philosophy. Simply reducing P and K fertilizer rates across all conditions during times of high prices is not a good nutrient or business management decision process. Soil-test range § ppm ft ra Summary Soil-Test Category Nutrient Soybean Yield ‡ 50 25 0 -25 -50 -75 -100 VL L O 0 10 20 H VH 30 40 Soil-Test Classes VL L O H 0 10 20 30 50 60 70 SOIL-TEST P (Bray-1, ppm) VH 40 Soil-Test Classes 50 60 Figure 1. Net returns to P application for different soil-test P levels and crop/fertilizer prices. 70 258 — 2008 Integrated Crop Management Conference - Iowa State University OPTIMUM INITIAL P ANNUAL P2O5/acre = 0 = 23 = 46 = 69 70 50 VERY HIGH INITIAL P Annual P stopped Annual P stopped Angela Rieck-Hinz, Extension Program Specialist, Agronomy, Iowa State University Introduction 20 Rising commercial fertilizer prices have caused manure nutrients to become a valuable and much sought-after commodity. Crop producers that have not traditionally used manure as a nutrient source for crop production are now looking to use manure to replace all of some of their commercial fertilizer inputs. Livestock producers are also looking for a way to capitalize on increasing feed input costs by selling manure. 3 6 9 12 15 18 21 24 27 0 3 6 Years of Cropping 9 12 15 18 21 24 27 ra Low Soil Test, High Likelihood of a Large Crop Response 600 500 $2.5/bu CORN $0.60/lb K2O $5/bu CORN $0.45/lb K2O $7.5/bu CORN $0.30/lb K2O 400 300 200 100 d 25 60 40 50 75 100 25 50 75 100 25 Fertilizer Application Rate (lb K2O/acre) 50 75 100 Optimum Soil Test, Low Likelihood of a Small Crop Response $7.5/bu CORN $0.30/lb K2O $5/bu CORN $0.45/lb K2O $2.5/bu CORN $0.60/lb K2O 20 0 -20 -40 -60 -80 -100 30 60 120 180 30 60 120 180 30 60 Fertilizer Application Rate (lb K2O/acre) 120 180 Figure 3. Examples of net returns to K fertilization in soils with large and small corn yield response to application according to the soil-test K level. Component pricing The most common method of valuing fertilizer is component pricing. The manure is sampled and analyzed to determine the nutrient content. This analysis is used to determine the value based on commercial fertilizer prices. A typical hog finishing manure might test 50-35-25 pounds of Nitrogen (N), Phosphorus (as P2O5), and Potassium (as K20) per 1,000 gallons. If the manure was injected with minimal losses and the nitrogen was readily available a 3,000 gallon rate would provide 140 pounds of nitrogen per acre. If N was valued at $0.70 a pound there would be $98 of N value. In addition you have 105 pounds of P2O5, and if valued at $0.85 per pound, would equal $89 per acre. You would also receive 75 pounds of K2O valued at $0.70 per pound or $52 per acre. That would bring the total to about $240 per acre. In addition the manure would contain other components such as sulfur, iron and organic matter. This method may not take into account potential nutrient losses and crop utilization. If one has very high phosphorus or potassium soil test levels the application of additional fertilizer may not provide any additional yield increases. One also needs to be cautious if entering into a long term agreement based on fertilizer values that are at 3 to 4 times historic prices. ra 0 d 10 ft 30 Figure 2. Change in soil-test P over time with different initial soil-test levels and P fertilizer rates for corn-soybean rotations. Net Return to K ($/acre) Manure: The new commodity 40 0 Net Return to K ($/acre) 2008 Integrated Crop Management Conference - Iowa State University — 259 Kelvin Leibold, Extension Farm Management Field Specialist, Iowa State University ft Soil-Test P (ppm) 60 Bulk commodity Another method used to price manure is to price it as a bulk commodity where you have sellers and buyers. If you are in an area that has an abundance of supply and limited demand it will drive the price down. If demand outstrips supply it will bid up the price until it balances out with the demand. The nutrients would have a different value depending on the location and local situation. Transportation and distribution costs become a factor in what the value is and how much the buyer can negotiate on price. If there is an over abundance of manure in one area and the livestock producers are faced with high transportation costs to move it out of the area they may be willing to reduce the price if they can avoid significant transportation costs. Dry poultry manure with high phosphorous levels lends itself to greater transportation distances because of the high nutrient density. ft If you use $.015 per gallon as a base rate a producer might spend $45 per acre to get manure applied. Even if there was a surcharge of $.002 per mile for going each extra mile it would only add $6 or $12 to the cost of going an extra mile or two. Comparing that cost with the $240 of potential value in the manure explains some of the excitement about constructing new hog finishing facilities by farmers that just produce grain. ra Some producers may decide to haul their own manure. This could be a crop producer who wants to haul someone else’s manure to his own farm or it could be a livestock producer. If the farmer already has a tractor that is adequate for pulling an applicator there are additional opportunities for savings. If producers are interested in calculating their own costs they can download http://www.extension.iastate.edu/agdm/crops/xls/a3-29machcostcalc.xls which is a spreadsheet that will help them calculate the fixed and variable costs of operating machinery. As the spreadsheet demonstrates, a person who uses a tractor that they already are using in their crop operation can lower the fixed costs and overall costs of hauling manure. Limitations d Some of the concerns with using manure are compaction from application, uniformity of the product, uniformity of application, fixed analysis, impact on planting date, increased weed pressure, or increased disease pressure to name a few. The “net present value” of applying phosphorus and potassium on very high testing soils may not equal the cost of the application. Manure is not always a uniform product. Even from year to year we are seeing differences in manure analyses because of changing animal diets that include phytase, dried distiller grains and synthetic amino acids. These rations can potentially have a lower nutrient analysis making them less value on a per 1,000 gallon basis. This also increases the cost of application per unit of fertilizer. This highlights the importance of a good manure nutrient analysis program. Other things to consider may include the need for your fields to be documented in a manure/nutrient management plan on file with the DNR, application separation distances, implementation of the Iowa P Index and other requirements. Valuing manure In the past we didn’t sell manure in Iowa. More frequently were trying to negotiate for the reimbursement of the cost of hauling. When dealing with liquid hog manure most of the hog operators were receiving between $0 and $20 per acre to offset the cost of hauling. This may change as fertilizer costs increase. Pork producers that have faced high feed costs are now trying to increase their revenue by selling the nutrients in the manure. Some are trying to get to where they would receive two-thirds of the nutrient value equivalent of fertilizer. There are some spreadsheets available to help calculate the value of manure as a fertilizer. One of the products is the ISU Manure Nutrient Value Calculator. The order form is available at http://www.ipic.iastate. edu/information/MNV.orderform.pdf. The spreadsheet compares the value of commercial fertilizers with manure. It also estimates the acres needed. It includes the Iowa P-Index formulas and summary reports. There is also a downloadable spreadsheet from the ISU Extension site at http://www.extension.iastate.edu/agdm/ livestock/xls/b1-65manurecalculator.xls. Another manure calculator spreadsheet is available to download from Bob Koehler’s web site at the University of Minnesota: http://swroc.coafes.umn. edu/Bob/koehler_main_page.html. Manure has a lot of valuable nutrients. It can be very cost effective to haul where needed. It is important to utilize the nitrogen component. A producer needs to know the quantity of manure available, the nutrient analysis of the manure, the crop needs, the current soil tests and the handling and application costs. The application of manure may result in increased or decreased yields when compared to traditional fertilizers depending on anyone of a number of reasons. The crop producer needs to predict how well they can manage the manure and what the overall impact will be over a number of years. You will then be better able to determine the value of the manure in your farming operation. ft Transportation costs can be broken down into to general categories. The first is commercial or custom hauling. Iowa has developed a very significant and important industry around commercial hauling for both liquid and dry manure. Commercial haulers usually base their rates on a per gallon basis, with a variety of premiums and discounts. Premiums are based on distance, rates, and set up fees to name a few. 2008 Integrated Crop Management Conference - Iowa State University — 261 Manure transportation and application The costs of transporting and applying manure usually fall into two general categories. The first is hiring it custom-applied. The second is to do it yourself. There are advantages and disadvantages to both. You may want to compare the costs of both methods. ra Transportation costs With commercial haulers you know fairly close as to what the cost per acre will be for the application costs. You don’t have any investment in equipment or any of the issues of dealing with hired labor. On the other hand you have less control over the timing of the work, the quality of the work, and the skill used in agitation and application of the nutrients. On the other hand you may have access to better equipment with better technology such as flow meters and auto steering than if you used your own equipment. The application may be quicker and timelier than if you do it yourself. Some of the liability associated with the application of manure may be shifted to the commercial hauler when transporting on public roads. d 260 — 2008 Integrated Crop Management Conference - Iowa State University Commercial hauling rates vary depending upon the supply and the demand for the service. Other factors that become a part of the rate that commercial haulers charge include the total number of gallons to be hauled, the application rate per acre, the amount of agitation, the distance to haul, the type of application or injection, the technology used, and the season of the year. Rates will also vary depending on the application method such as the use of an umbilical system, semi tanker transfer system, or dry handling system. They may also include such things as “fuel price” increases that are passed through. Fixed and variable costs Whether you are a commercial hauler or a private hauler you can break the costs down into two general areas. The first is fixed costs and the second is variable costs. These are often known as the DIRTI FIVE - Depreciation, Interest, Repairs, Taxes, and Insurance. ra For someone looking at getting started in the commercial manure hauling business they would want to try to identify the expenses and income potential. You would have significant investment in tractors, tankers, and agitation equipment and support vehicles to name just a few of the capital items. You would also have expenses in overhead, labor, repairs, fuel, fuel transportation, taxes, insurance and certification fees. d You can use spreadsheets to give you some general ideas about what the costs might be. One example is ISU Machinery Cost Calculator found at http://www.extension.iastate.edu/agdm/crops/ xls/a3-29machcostcalc.xls that will help calculate costs. If you assume that you use a $180,000 tractor to pull a $80,000 manure tank wagon and you use it for 500 hours a year for ten years, the cost of interest is 6%, labor costs $13 per hour, fuel at $3.50 per gallon and you cover 2000 acres in a season it would cost $13.23 per acre to own the two pieces plus $22.40 per acre to operate it for a total cost of $37.21 per acre or a total cost of $74,418. This doesn’t include any of the agitation equipment or overhead expense. It includes the interest and depreciation, taxes, insurance, repair costs, fuel, and labor. If you applied 3,500 gallons of nutrients per acre and charged a penny a gallon you would generate $35 per acre or $70,000 in revenue leaving you with a significant shortfall by the time you added in all of the overhead costs. If you applied on 5,000 acres with the same rig and did that in 909 hours of work your total costs for the two pieces of equipment would drop to $23.41 per acre or a total of $117,064. If you charged $35 on 5,000 acres you would generate $175,000 and be able to start to cover some of the other expenses. One of the major variables is accurately estimating the number of gallons that you will haul and the time to do that. A spreadsheet that may be useful in doing that is the Estimating Field Capacity of Farm Machines found at http://www.extension.iastate.edu/agdm/crops/ xls/a3-24fieldcap.xls. It can help you estimate the acres you can cover and the time to do it. It also helps you think about the speed you travel, the size of your toolbar and the turnaround time or efficiency. You would then need to go through the list of equipment and other overhead expenses and estimate your costs for the other items to see if there might be enough income to pay all of the cash and non-cash costs and have a reasonable return to management. Many commercial haulers have underestimated the expenses and overestimated the revenue resulting in haulers exiting the industry. One other item of concern is to set a fee structure that takes into count some of the variables you may encounter such as hauling farther distances or excessive road time in between sites. You may also have down time due to the time required for agitation, breakdowns or weather delays as well. For example, if you increase the hauling distance from one mile to two miles it can increase your time to make a round trip by 40%. If you increase the hauling distance from 2.5 miles to 3.5 miles the time requirement might increase by 25%. Commercial haulers typically get paid by the gallons that go through the meter and if you increase your trip time by 25% you will decrease your revenue per hour by 25% so rates need to reflect that. ft Calculating costs ft Variable costs are those costs that you pay when you operate. Fuel is a major cost along with repairs. Repairs can vary tremendously depending upon the age of the equipment, the skill of the operator, the maintenance program and the type of use. Wagons that spend a lot of time on the road will have accelerated tire wear. Operators that drive through ditches and ravines will have more repairs. Operators who operate at night tend to have higher repairs as well. Deeper injection may require more fuel than shallow or surface application. 2008 Integrated Crop Management Conference - Iowa State University — 263 If you are hauling your own manure and you already have your own tractor and labor is not a restraint the cost of hauling may be less. Your ownership costs for the tractor will be spread out over more hours. However, you need to watch what your investment in the manure tank wagon is because if it is a large investment and you don’t use it on a lot of acres the tractor savings may be more than offset by the increased ownership costs of the tank wagon. If that is the case one might be able to lower the costs by looking at joint ownership or short term leasing of the item. ra Fixed costs are the costs that you incur because you are involved in the activity. You have start up costs such as licensing fees if you need one. You may also need liability insurance. The fixed costs include depreciation and opportunity costs which are part of the machinery costs. A large manure tank wagon is going to sit still more days than it will be used unless you travel from state to state. A manure tank wagon could cost well over $75,000 and the tractor another $175,000 or more. Then there are the agitation pumps and service vehicles. A commercial hauler with three rigs and support equipment could have well over $1,000,000 of equipment that is depreciating and tying up capital. If you were looking at spreading dry manure you would go through the same process. You might be looking at a semi tractor, a side dump trailer, a loader, and a spreader. You might also have some significant overhead costs such as insurance, licensing and employment taxes. With higher fertilizer prices it will pay to haul manure farther if you need to better utilize the nutrients on lower testing fields. You need to use the fertilizer in the most environmentally sustainable method. You need to utilize soil tests in making decisions about where to apply and how much to apply. It may be more economical to apply lower rates based on phosphorus and supplement the nitrogen to better utilize the phosphorus and potassium over more acres. We need to test the manure and understand the variability of the content of the nutrients that can occur. d 262 — 2008 Integrated Crop Management Conference - Iowa State University Selling and buying manure As with anything related to manure in Iowa, there are rules, regulations and requirements for selling and buying manure. Regulatory requirements for selling manure in Iowa are highly correlated to the need for a manure or nutrient management plan and the type of facility that is producing the manure. If you are planning to buy manure produced outside of Iowa or sell manure to someone located outside of Iowa, please be sure to check the regulatory requirements of other states. Sales or distribution of manure is regulated by either the Iowa Department of Natural Resources (IDNR) or the Iowa Department of Agriculture and Land Stewardship (IDALS). 264 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 265 Selling manure from confinement facilities that require a manure management plan manure applicator and you will be required to be certified as a commercial manure applicator. Manure from confinement facilities requiring a manure management plan may be sold under one of four methods and still meet manure plan requirements. These methods are defined by the type of manure being sold. This method is very similar to Method 3, but does not require a formal manure management plan. However, the requirements include all of the components of a manure management plan. If your operation has an established practice of selling manure or includes a type of livestock for which selling manure is a common practice, you must submit the following information to the DNR: estimate of number of acres required for land application of manure from your farm; annual animal production; manure volume generated; manure sales form; a statement of intent from the purchaser(s) or past sales records and, if required the Iowa P Index and factors used in the Iowa P Index calculations. The DNR does not require use of specific forms for the sale of manure or the statement of intent to purchase manure, but links to examples may be found in the Additional Resources section at the end of this fact sheet. The owner of the manure shall maintain copies of the current manure management plan and signed copies of the sales forms from each purchaser for five years after each sale. d ra This is the most common method for selling dry manure. Manure that meets the definition of “dry” manure can be sold under Chapter 200A which is regulated by IDALS. The difference between Chapter 200 and 200A is that dry bulk animal nutrient product is defined as any unmanipulated animal manure sold in bulk form to which a label cannot be attached, the manure contains one or more recognized plant nutrients, the manure promotes plant growth, the manure does not flow perceptibly under pressure, the manure is not capable of being transported through a mechanical pumping device designed to move liquid and the constituent molecules of the manure do not flow freely among themselves, but do show a tendency to separate under stress. Manure sold under Chapter 200A requires a guaranteed analysis. Manure sold through Chapter 200A does not require implementation of the Iowa Phosphorous Index. However, a copy of the IDALS license and the DNR manure management plan form for the sales of dry manure must be submitted to the DNR in place of the regular manure plan forms. Manure sold under Chapter 200A does not require secondary containment. Method 3. Distribution of Manure through a Manure Agreement. If you choose not to sell manure via method 1 or 2 as identified above, or if you plan to sell liquid manure from a confinement facility, you may do so through a manure agreement. In this case, you as the seller complete a manure agreement with the purchaser for either the cost of the manure or the cost of application of the manure or the cost of both. For this method you will be required to meet the application rate limits and conditions of your manure management plan as required by the DNR( DNR Form 542-4000) . This will include implementing the Iowa Phosphorus Index on all fields receiving manure through the agreement. In addition, the purchaser of manure is required to keep records of commercial fertilizer application to ensure nutrient application rates in the manure management plan are not exceeded. The purchaser of the manure is required to share these records with the owner of the manure management plan on an annual basis. One example for keeping these records includes the DNR Form 542-8167, “Statement of Intent” to report planned applications of commercial fertilizer to the DNR. Use of this form is not required. It should also be noted that if you as the manure generator, charge for the application of manure from your farm to others, the DNR considers you to be a commercial ft Method 2. Selling Manure under Iowa Code Chapter 200A or the “Bulk Dry Animal Nutrients Products Law.” Selling manure from confinement facilities that do not require manure management plans If you are not required to have a manure management plan, you may sell manure via methods 1 or 2 above if it is dry manure, or via a private contract. It is not necessary to have a private contract, but is possible the purchaser could sue the seller if the product fails to meet expectations for its intended use, therefore implementing a contract can help to protect the seller. ra ft Manure may be sold under Chapter 200 of the Iowa Administrative Code which is regulated through IDALS. Manure sold under Chapter 200 is manure that has been manipulated in some manner, such as having other ingredients added, being dried or composted or being bagged for commercial distribution. Manure sold under Chapter 200 requires secondary containment around the manure storage structure. Manure sold under Chapter 200 requires a guaranteed analysis. A copy of the IDALS license and the DNR manure management plan form for the sales of manure must be submitted to the DNR in place of the regular manure plan forms. Selling manure from permitted open feedlots The DNR has no regulations on selling manure from permitted open feedlots, so you will be required to comply with all DNR requirements pertaining to a Nutrient Management Plan. So, similar to manure from confinement feeding operations, manure will have to be distributed and or sold through manure agreements as part of the nutrient management plan. (See methods 3 or 4 above). d Method 1. Selling Manure under Iowa Code Chapter 200. Method 4. Distribution of Manure through Manure Sales Form. Selling manure from non-permitted open feedlots Because non-permitted open feedlots are not required to meet nutrient management plan requirements, there are no regulations for selling manure. They may choose to sell dry manure under Chapter 200 or 200A, but are not required to so. It may be beneficial to sell manure from these types of facilities via a private contract to protect the seller, but it is not necessary. A portion of this paper was adapted from Iowa Manure Manager Series, Volume 10, Buying and Selling Manure located on the WEB at http://www.agronext.iastate.edu/immag/pubsimms.html 266 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 267 Impacts of extreme precipitation events on performance of conservation practices Xiaobo Zhou, Postdoctoral Research Associate, Agricultural and Biosystems Engineering, Iowa State University Matthew J. Helmers, Assistant Professor, Agricultural and Biosystems Engineering, Iowa State University ra ft Climate-induced changes in the volume and erosive power of precipitation is the most important effect of global climate change on soil erosion and surface runoff (Nearing, 2001). Greater frequency and intensity of extreme weather events have been observed in the last decades due to the climate change (Milly et al., 2002; SWCS, 2003). One of the direct consequences of those extreme events on agricultural land is the acceleration of topsoil loss, which leads to soil degradation and pollutant transport from the field. A linearly increase of the amount of daily precipitation by 5% or 10% could increase soil erosion by 10.7% and 35.6%, respectively (Savabi et al., 1993). In addition, the risk of gully erosion and stream channel erosion are also increased during the extreme events. Consequently, a more severe and lasting damage to soil and water resources can be caused from these forms of erosion, which require more intensive and costly conservation treatments (SWCS, 2003). Soil erosion from cropland can be reduced by the implementation of conservation management practices, such as reduced tillage, crop rotation, residue management, vegetative filter strips, terraces, and grassed waterways (Baker et al., 2006). In current practice, the mean annual sediment yield over a long period has often been used to act as a targeted goal for the design and implementation of conservation systems. However, agricultural systems are more vulnerable to the effects of extreme climate events (Philpott, 2008), which usually largely contribute to erosion and sediment transport while the majority of the rainstorms play only a minor role (Coppus and Imeson, 2002). Therefore, conservation practices should be designed and implemented to resist the effects of extreme events of some designated return period, rather than the average annual events (Larson et al., 1997). d d ra ft Introduction With the extreme precipitation events in 2008 there is a need to review and estimate the performance of conservation practices. In this study, we used the Water Erosion Prediction Project (WEPP) model to simulate soil erosion with various tillage systems and conservation practices, and assess their performance in reducing sediment export from the extreme precipitation events. Material and fethods Site description Two farms in northeast Iowa were selected to investigate the impact of conservation practices on soil erosion from extreme storm events. One farm (site 1) was located in Winneshiek County, which had a 9% slope. The other farm (site 2) located in Delaware County had a 1.7% slope. The sizes of both farms were about 300 acres. The predominant soils were Downs silt loam and Clyde 268 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 269 silty clay loam for sites 1 and 2, respectively. Results and discussion WEPP model description Impact of tillage systems on annual sediment yield The Water Erosion Prediction Project (WEPP) model (version 2006.5) was used to simulate soil erosion and sediment yield (Nearing et al., 1989). The WEPP model is a process-based erosion prediction model for soil loss and sediment deposition for small watersheds and hillslopes. Many processes related to soil erosion are integrated in the WEPP model, including rill and interrill erosion, infiltration, percolation, sediment transport and deposition, surface runoff, residue and canopy effects, tillage effects, and evapotranspiration. The predicted mean annual sediment yields under various tillage systems were summarized in Table 1 for both study sites. As expected, more tillage produced greater sediment yield because of the less field residue cover. No-tillage and strip-tillage systems had much lower sediment yields than the other three tillage systems. WEPP default values were used for tillage and crop management parameters. Five tillage systems were simulated in this study, including no-tillage (NT), strip-tillage (ST), disk-tillage (DT), chiselplow (CP), and moldboard plow (MP). NT had no soil or crop residue disturbance except for that occurring during planting. ST prepared narrow rows for seed bed after soybean harvest in the fall while no-till was used after corn harvest. DT included a disking after corn harvest in the fall and field cultivating for both corn and soybean in the spring. CP consisted of chisel operation after corn harvest in the fall and field cultivating for both corn and soybean in the spring before planting. In MP, cornstalks were plowed with a moldboard plow in the spring before planting soybean, and soybean stubble was disked in the spring in preparation for corn planting. d For NT and CP, three additional erosion control structures were simulated: grassed waterways (GW), grass filter strips (FS), and terraces (T). Grassed waterways had a triangular shape with perennial grasses and a width of 3 ft. In FS simulation, a portion of row-cropped field was replaced with perennial grass at the bottom of each hillslope. The length of filter strips was 10% of the slope length. In terrace simulation, parallel narrow-base terraces had a width of 2.7 m and a uniform gradient of 0.5%, with a horizontal spacing of 30 m. The same field management was applied for the terrace as for the rest of the field. ft Table 1. Sediment yield and sediment delivery ratio of two study sites in northeast Iowa. Site 1 (9.0% slope) Sediment yield Site 2 (1.7% slope) Sediment yield (t/acre/yr) Sediment delivery ratio (t/acre/yr) Sediment delivery ratio 6.8 0.84 0.19 0.54 8.3 0.79 0.31 0.51 25.1 0.60 0.61 0.54 Chisel plow 31.0 0.59 1.00 0.51 Moldboard plow 45.9 0.68 2.39 0.48 No-till Strip-till Disk-till ra ra The simulations were performed in the Watershed mode. Each site was subdivided into three sub-areas (hillslopes) using the GeoWEPP, which is a geospatial interface for the WEPP model (Renschler, 2003). The slopes of each hillslope were derived from the 30-m digital elevation data. In the simulations, flow channels were naturally eroded and had the same field management as the rest of the field, unless specified otherwise. The steepness of slopes had significant impact on soil erosion. The simulation results showed that the site with greater slope (9%) (site 1) had much higher annual sediment yield than the site with 1.7% slope (site 2) (Table 1). Site 1 also had higher sediment delivery ratios (the ratio of sediment yield to the total sediment eroded) than site 2, regardless of the tillage systems. Due to its steep slope, even the no-tillage system had a higher annual sediment yield (6.8 t/acre) than the commonly-used target value (5 t/acre). Therefore, additional conservation structures may need to be adopted in this site (e.g. filter strips, terraces, etc). d ft Four main data inputs are required by the WEPP model: climate, topography, soil and management. The climate generator, CLIGEN, was used to create the 50-year climate files for each study site. The historical weather data from the City of Decorah in Winneshiek County was used to create the climate input file for site 1, and the weather data from the City of Oelwein in Fayette County was used to create the climate input file for site 2. Impact of tillage systems on sediment yield during extreme precipitation events Return period analysis The simulation results showed that large precipitation events would lead to much greater surface runoff volumes and soil erosion rates regardless of tillage system. For example, the surface runoff of a disk-tillage system was estimated to be about 1.9 inches for a 2-year event and 4.6 inches for a 25-year event. Likewise, the sediment yield of a disk tillage system was estimated to be 12.5 and 46.9 t/acre for a 2-year and 25-year event, respectively (Table 2). The return period analysis implemented in the WEPP model was used to estimate the magnitudes of surface runoff and sediment yield during the extreme events (2-year, 5-year, 10year, 20-year and 25-years events) under different tillage systems and erosion control structures. The return period is the average elapsed time between occurrences of an event (e.g. rainfall, runoff, sediment yield) with a certain magnitude or greater (Haan, 1977). Over a long period of time, for example, a 10-year event has a probability of 10% of being equaled or exceeded in any one year. There was only slight difference in surface runoff among different tillage systems for simulated extreme events. However, a reduced tillage, such as no-tillage or strip-tillage could greatly reduce soil erosion and sediment yield during the extreme events. The effect of reduced tillage systems on sediment reduction was even more evident for the events with longer return period, i.e. larger precipitation events. For example, the sediment yield in the simulated no-tillage system was reduced by about 14 t/acre and 62 t/acre during a 2-year and 25-year event, respectively, comparing to the moldboard plow tillage system (Table 2). Surface runoff Sediment yield (inch) (t/acre) 2 3.0 1.9 4.5 5 4.0 3.0 5.9 10 4.5 4.0 6.5 20 4.9 4.2 7.2 25 6.0 4.7 7.7 2 3.0 1.9 5.3 4.0 2.9 6.7 4.5 4.0 7.9 4.9 4.2 8.6 6.0 4.7 8.9 3.0 1.9 11.3 4.0 3.0 18.4 10 4.5 3.8 28.1 20 4.9 4.2 33.8 25 6.0 4.6 42.5 2 3.0 1.9 13.7 5 4.0 3.0 22.9 10 4.5 3.8 36.3 20 4.9 4.2 45.1 25 6.0 4.6 58.2 2 3.0 1.9 18.9 5 4.0 3.0 31.2 10 4.5 3.8 47.0 20 4.9 4.2 54.2 25 6.0 4.6 69.9 5 Strip-till 10 20 25 2 ra 5 Disk-till d Chisel plow Moldboard plow Performance of erosion control structures during extreme precipitation events For a no-till system, grassed waterways showed relatively small impacts on sediment reduction during extreme events (Figures 1 and 2). This is likely because the high-percentage field residue cover from a no-tillage system has already greatly reduced the sediment load in surface runoff before the water enters into the flow channels. Note that an extreme sediment event of a specific return period with or without grassed waterways implemented, may not necessarily respond to the same precipitation event. That could cause a slightly greater sediment yield with grassed (a) (b) Figure 1. Performance of grassed waterways at site 1 under a corn-soybean rotation with (a) no-till and (b) chiselplow during the extreme storm events. ra Daily precipitation (inch) ft Return period (year) waterways under no-tillage system due to the relatively narrow range of sediment yield. For a chisel-plow system, on the other hand, grassed waterways reduced sediment yield to a great extent at both study sites, especially during the 10, 20, and 25 year return periods (Figures 1 and 2). d Table 2. Return period analysis for different tillage systems at site 1. No-till 2008 Integrated Crop Management Conference - Iowa State University — 271 ft 270 — 2008 Integrated Crop Management Conference - Iowa State University (a) (b) Figure 2. Performance of grassed waterways at site 2 under a corn-soybean rotation with (a) no-till and (b) chiselplow during the extreme storm events. Similar to grassed waterways, grass filter strips greatly reduced sediment yield with chisel-plow tillage system, but had relatively small impacts on sediment yield with no-tillage system from the extreme events (Figures 3 and 4). Comparing to results from site 2, the effect of filter strips on trapping sediment at site 1 during the extreme events was greater because of the higher sediment loading in surface runoff at steep site 1. 272 — 2008 Integrated Crop Management Conference - Iowa State University (b) (a) (b) d Figure 4. Performace of filter strips at site 2 under a corn-soybean rotation with (a) no-till and (b) chisel-plow during the extreme storm events. Terraces were effective in sediment reduction at the steeper site 1 with both the no-tillage and chisel-plow systems (Figure 5). The increases of sediment yield during some extreme events with a no-tillage system at site 2 might be because the inter-rill flow and erosion are more critical than rill erosion for a no-tillage system (Figure 6). As a result, the WEPP model did not do a good job in simulating the impact of terraces by reducing slope length for a no-tillage system, especially for flat areas, but overall there were relatively low levels of simulated soil erosion at site 2. (b) ft Figure 5. Performace of terraces at site 1 under a corn-soybean rotation with (a) no-till and (b) chisel-plow during the extreme storm events. ra ra Figure 3. Perfomance of grass filter strips at site 1 under a corn-soybean rotation with (a) no-till and (b) chisel-plow during the extreme storm events. (a) (a) (b) Figure 6. Performace of terraces at site 2 under a corn-soybean rotation with (a) no-till and (b) chisel-plow during the extreme storm events. d ft (a) 2008 Integrated Crop Management Conference - Iowa State University — 273 Conclusions The performance of conservation practices during extreme precipitation events is very critical to assess their effectiveness on soil erosion control. The return period analysis from the WEPP model simulation showed that reduced tillage systems can greatly reduce soil erosion and sediment yield by increasing field residue cover during extreme events. Additional erosion control structures (grassed waterways, filter strips and terraces) were very effective in reducing sediment yield from extreme events for croplands with a high soil loss potential, such as steep slopes, intense tillage, or highly erodible soils. References Baker, J.L., M.J. Helmers, and J.M. Laflen. 2006. Water management practices rain-fed cropland. p. 89-130. In M. Schnepf and C. Craig (ed.) Environmental benefits of conservation on cropland: the status of our knowledge. Soil and Water Conservation Society, Ankeny, IA. Larson,W.E., M.J. Lindstrom, and T.E. Schumacher. 1997. The role of severe storms in soil erosion: A problem needing consideration. Journal of Soil and Water Conservation 52: 90-95. Milly, P.C.D., R.T. Wetherald, K.A. Dune, and T.L. Delworth. 2002. Increasing risk of great floods in a changing climate. Nature 415: 514-617. ft Nearing, M.A. 2001. Potential changes in rainfall erosivity in the U.S. with climate change during the 21st century. Journal of Soil and Water Conservation 56: 229-232. Philpott, S. M., B. B. Lin, S. Jha, and S. J. Brines. 2008. A multi-scale assessment of hurricane impacts on agricultural landscapes based on land use and topographic features. Agriculture, Ecosystems and Environment 128: 12-20. ra Savabi, M.R., J.G. Arnold, and A.D. Nicks. 1993. Impact of global climate changes on hydrology and soil erosion: A modeling approach. Pp. 3-18. In: Y. Eckstein and A. Zaporozec (eds.). Proceedings of Industrial and Agricultural Impacts on the Hydrologic Environment, Vol. 3, Impact of Environmental and Climatic Change on Global and Regional Hydrology. Water Environment Federation, Alexandria, Virginia. d Soil and Water Conservation Society (SWCS). 2003. Conservation implications of climate change: Soil erosion and runoff from cropland. A report from the Soil and Water Conservation Society. Effect of cover crops in reducing nitrate-nitrogen leaching in Iowa Zhiming Qi, Graduate Research Assistant, Agricultural and Biosystems Engineering, Iowa State University Matthew J. Helmers, Assistant Professor and Extension Agricultural Engineer, Agricultural and Biosystems Engineering, Iowa State University Introduction Nitrate-nitrogen (NO3-N) has been deemed a main source of pollutant for both shallow groundwater and surface water bodies. The main source of NO3-N in the Mississippi River Basin (MRB) is linked to tile drainage (Lowrance, 1992; David et al., 1997). Approximately 25% of agricultural land is artificially drained in Iowa (Baker et al., 2004) and subsurface drainage is the main source of NO3-N loss. Schilling and Zhang (2004) reported that while Iowa accounts for 5% of the area of the MRB it contributes approximately 25% of NO3-N load (23 lb-N acre-1) over a 28-year period from 1972 to 2000. Plot scale experiments measured NO3-N loss of 23 to 49 lb-N acre-1 year-1 in northeast Iowa (Weed and Kanwar, 1996), 24 to 27 lb-N acre-1 in central Iowa (Baker et al., 1975; Baker and Johonson, 1981; Kanwar et al., 1983) and 6 to 56 lb-N acre-1 year-1 in northwest Iowa (Lawlor, et al., 2008). ft Haan, C.T. 1977. Statistical methods in hydrology. Iowa State University Press, Ames, Iowa. 2008 Integrated Crop Management Conference - Iowa State University — 275 ra Coppus, R. and A. C. Imeson. 2002. Extreme events controlling erosion and sediment transport in a semi-arid sub-andean valley. Earth Surface Processes and Land Forms, 27: 13651375. The mass of NO3-N loss is closely related to subsurface drainage volume (Baker et al, 1975; Cambardella et al., 1999). April, May and June were found to be the main subsurface drainage period. In these 3 months, nearly 70% of the drainage occurred in north-central Iowa (Helmers et al., 2005), and 71% of the annual drainage and 75% of NO3-N loss were observed in Minnesota during this period (Randall and Vetsch, 2005). Annual cover crop, perennial living mulch and perennial grassland have the potential to reduce NO3-N leaching in the Midwest. Annual winter cover crops, which have historically been added into corn-soybean rotation to achieve soil and water conservation benefits in the Midwest (Kaspar et al., 2001; Unger and Vigil, 1998), were studied to assess their potential in reducing subsurface drainage volume and NO3-N concentration in the drain flow thereby decreasing the NO3-N loss from the soil. Strock et al. (2004) found that using rye as a winter cover crop in Minnesota reduced drainage water by 11% and NO3-N leaching by 13%. In a 4-year field experiment conducted in Iowa, Kaspar et al. (2007) reported that average annual NO3-N loss from winter rye cover treatment was 17.7 lb-N acre-1 which was 61% lower than the control treatment, and that N uptake by rye was as high as 43 lb-N acre-1 with a fertilizer rate of 210 lb-N acre-1 and 220 lb-N acre-1 to corn in a corn-soybean rotation. Italian ryegrass, alfalfa, and kura clover are examples of living mulches. Perennial grassland serves as an effective nitrogen loss reduction approach because no fertilization is necessary and it has a longer growing period than winter cover crop, however at present there is little economic market for the product. Baker and Melvin (1994) documented that the NO3-N concentration in the drain tile under alfalfa was much lower than that under corn or soybean. d 274 — 2008 Integrated Crop Management Conference - Iowa State University In Iowa previous research on NO3-N loss with rye as a winter cover crop were conducted with relative high N rates (Kaspar et al., 2007). Reports on perennial living mulch as an approach of water quality protection is very limited. To get a better understanding on the effects of land 276 — 2008 Integrated Crop Management Conference - Iowa State University covers on NO3-N loss, a field experiment was conducted in northwest Iowa with winter rye cover crop in corn-soybean rotation, kura clover as a living mulch for corn and a pasture land cover. The objectives of this study were: 1) to evaluate the impact of a different land covers on NO3-N loss in subsurface drainage under a recommended crop fertilization; 2) to investigate the NO3-N concentrations in the soil water under different land covers and 3) to quantify the N uptake by different cover crops in the spring. 2008 Integrated Crop Management Conference - Iowa State University — 277 in spring closely following corn emergence to corn plots only. See Table 2 for agronomic timing details. Drainage volume monitoring, sampling and analysis Soil water solution and biomass sampling The field study was conducted from 2006 to 2008 on the Agricultural Drainage Water Quality - Research and Demonstration Site (ADWQ-RDS, former Agricultural Drainage Well Site) near Gilmore City in Pocahontas County which has been described in greater detail by Helmers et al. (2005), Singh et al. (2006) and Lawlor et al. (2008). An automatic meteorological station was installed at the site. The size of each plot was 125 feet in length and 50 feet in width. The plots were established after the installation of corrugated plastic drain tiles through the center and both boundaries parallel to the long dimension (25 feet Spacing) at a depth of 3.5 feet. All subsurface drainage lines extended to one of the two sumps where water was collected and pumped into a nearby wetland. Drainage water from each center line is collected in an aluminum culvert with automatic pumping, volume monitoring and water sampling systems. Soil water solution was sampled using two suction lysimeters (3 feet apart) installed along the median line between the center and boundary lines at the depths of 1 and 2 feet in each of the medium high, medium low and low flow block plots. A vacuum of -10.8 psi was applied to the suction lysimeters every week and any available soil water solution sample was collected every three to four days. Soil solution samples were processed and analyzed in the Agricultural and Biosystems Engineering Water Quality Laboratory, Iowa State University using a Quickchem 2000 Automated Ion Analyzer flow injection system (Lachet Instruments, Milwaukee, Wisc.). Rye shoots were sampled weekly from early spring until chemically desiccated by roundup. Weekly kura clover and pasture shoots sampling coincided with rye and continued until late June. From July, corn, soybean, kura clover and pasture were sampled once every three weeks until early October. Rye, corn and soybean were sampled along a 1-foot long section at four randomly selected locations; Kura and pasture were sampled in a 1×1 foot2 area randomly selected at three locations in each plot. Samples were dried at 140 F for a week in ovens at the Agricultural Engineering Farm of Iowa State University. Dry matter weight was recorded. Total nitrogen (TN) content was analyzed for all samples obtained from rye plots, two occasions for Kura clover and pasture, and two occasions for corn soybean plots. Total nitrogen analysis was conducted in Soil Plant Analysis Laboratory at Iowa State University by the combustion method. TN for the plant shoots of 2008, which is still in process, is not available. Agronomic management Agronomic field activities were completed in a timely manner prior to and during the crop season beginning in October 2004 with plot tillage and rye seeding. Tillage for seedbed preparation for perennial crops was completed in the spring just prior to planting on April 18, 2005. ‘Endura’ kura clover (Trifolium ambiguum) was hand seeded at a rate of 11.6 lb acre-1, the perennial pasture plots were hand seeded with ‘Duration’ red (Trifolium pratense), and ‘Pinnacle’ ladino (Trifolium repens)clovers with ‘Extend’ orchardgrass (Dactylis glomerata) at 8.0, 0.5, and 4.0 lb acre-1, respectively. ‘Rymin’ rye (Secale cereale) was drill seeded at a rate of 89.2 lb acre-1 in 7.5 inches rows with a skip row every 30 inches for subsequent corn or soybean planting in the spring. Commercial-grade 28% aqueous ammonia-nitrogen (N) was applied at 125 lb-N acre-1 ra Statistical analysis Subsurface drainage volume, flow-weighted NO3-N concentration in the subsurface drainage, NO3-N loss and NO3-N concentration in the suction lysimeter were analyzed as a completely randomized block design using PROC GLIMMIX procedure in SAS software which can test the significance of difference for unbalanced data. Means were grouped using a least significant difference test at p=0.05 (LSD0.05). d ra d A six-treatment experiment was established in a completely randomized block design. The six land cover treatments in 2006, 2007, and 2008 were (Table 1): 1) corn-soybean rotation initiated with corn in 2006 with fallow in spring (fallow-Corn-fallow-Soybean-fallow-Corn, fCfSfC); 2) corn-soybean rotation initiated with soybean in 2006 with fallow in spring (fallow-Soybeanfallow-Corn-fallow-Soybean, fSfCfS); 3) corn-soybean rotation initiated with corn in 2006 with rye cover crop (rye-Corn-rye-Soybean-rye-Corn, rCrSrC); 4) corn-soybean rotation initiated with soybean in 2006 with rye cover crop ( rye-Soybean-rye-Corn-rye-Soybean, rSrCrS); 5) Corn with established kura clover as a living mulch (kura-Kura-kura-Corn-kura-Corn, kKkCkC); and 6) Pasture as a perennial grass treatment (PP). The plots were blocked by drainage characteristics, resulting in 4 blocks as high drainage, medium high, medium low and low blocks based on the long-term drainage performance. One plot in each block was randomly assigned to each treatment (6 treatments×4 blocks×1replication) in this study. This experiment was initiated in 2005 but data presented in this paper started in April 2006 since 2005 was considered a transition year due to previous plot treatments. ft Site description ft Materials and methods Drainage flow volume was measured by a magnetic flow meter, connected to an electronic data logger. Meter readings were also recorded manually. Samples were collected after every 0.5 inch of subsurface drainage flow, and thereafter were stored in a cooler at 39oF until analyzed. NO3-N concentration was analyzed in the Wetland Research Laboratory, Iowa State University through the second-derivative spectroscopy technique. Results and discussion Precipitation and temperature Daily precipitation and temperature for the study period are presented in Fig 1. The annual precipitation in 2006 and 2007 was 21.6 and 33.7 inches respectively, with 21.0 and 33.1 inches in the drainage season from March to November. The total precipitation in 2008 until July was 24.0 inches. The long term average rainfall in the drainage season for Pocahontas, Iowa, was 28.4 inches (Lawlor et al., 2008). The long-term monthly average temperatures during the rye growing season in March, April, and May are 33.8o, 47.5 o and 60.0 oF. The temperatures during ft The annual discharge for the 24 plots varied from 1.2 to 9.4 inches in 2006, 4.1 to 39.8 inches in 2007, and 3.5 to 35.7 inches in 2008 (Table 3, 4, and 5). The average annual drainage of all land cover treatments was 13.4 inches during the three years observation, which represented 51.4% of the rainfall during the drainage season. The total average drainage in April, May and June was 8.7 inches which accounted for 65.0% of the annual drainage while 81.5% of the total rainfall occurred in these three months. There was no significant difference in monthly or annual drainage volume due to land cover treatments except that the drainage of kKkCkC in May 2007 was significantly lower than fSfCfS, fCfSfC, and rSrCrS treatments. ra NO3-N concentration in the tile drainage water samples varied from 3.5 to 21.9 mg N L-1 during 2006, 1.0 to 25.3 mg N L-1 in 2007, and 1.0 to 18.3 mg N L-1 in 2008. The average annual flowweighted NO3-N concentration of fSfCfS and fCfSfC treatments was 13.7 mg N L-1, and the value for rSrCrS and rCrSrC treatments was 12.2 mg N L-1. In the corn-soybean rotation plots no matter with or without winter rye as a land cover, monthly flow-weighted NO3-N concentration in April, May and June consistently exceeded the 10 mg N L-1 maximum contaminant limit set by the USEPA for drinking water. Treatments with rye followed by soybean in 2006 and 2007 showed the lowest annual flow-weighted NO3-N concentration for the corn-soybean rotation with a NO3-N concentration 21.7% lower than the treatments with fallow-soybean. Although significant annual NO3-N concentration reduction by rye was only observed in rSrCrS for 2006, the reduction of monthly NO3-N concentration was found in most cases during April, May and June of 2006 and 2007 (Table 3 and 4). d The average annual flow-weighted NO3-N concentrations from the drain tile of the kKkCkC were 6.7, 7.2, and 6.4 mg N L-1 for 2006, 2007, and 2008, respectively, and were 8.2, 4.8, and 3.4 N L-1 for PP treatment, below the 10 mg N L-1 of USEPA limit for drinking water. The annual flow-weighted NO3-N concentrations of kKkCkC treatments, even with fertilizer application on June 5, 2007 and June 20, 2008, was found to be significantly lower than the fSfCfS and fCfSfC treatments (p<0.05). NO3-N concentration in PP treatment decreased from 2006 to 2008 and was significantly lower than all treatments with corn-soybean rotation in 2007 and 2008 (p<0.05). The lowest annual flow-weighted concentration of 3.4 mg N L-1 was observed in PP treatment for 2008. The annual NO3-N loss of the 24 plots varied from 7.2 to 56.6 lb-N acre-1 for 2006 and from 6.5 to 96.2 lb-N acre-1 for 2007, and 6.5 to 77.3 lb-N acre-1 for 2008. The annual NO3-N loss was 36.3 lb-N acre-1 for fSfCfS and fCfSfC treatments, and 35.8 lb-N acre-1 for rSrCrS and rCrSrC treatments on average over the three years. The average total NO3-N loss during April, May, and June was 25.0 lb-N acre-1 for fSfCfS and fCfSfC, 59.6% of the annual NO3-N leaching. Rye followed by soybean grew around 20 days longer than that followed by corn due to the later planting date for soybean. While not significantly different there was some slight reduction in NO3-N loss during April, May and June for the winter rye cover crop treatment. In these three months, the average NO3-N loss for fSfCfS and fCfSfC was 25.0 lb-N acre-1 and 22.7 lb-N acre-1 for rSrCrS and rCrSrC. The average drainage volume was not significantly different over the three years (Table 6). The three-year flow weighted NO3-N concentration of kKkCkC and PP treatments were significantly lower than other treatments (Table 6). Average annual NO3-N losses from fSfCfS and fCfSfC were 40.0 and 32.7 lb-N acre-1, comparable to the values of NO3-N loss from rSrCrS and rCrSrC which were 34.5 and 37.0 lb-N acre-1. The average annual NO3-N loss of kKkCkC and PP treatments were 21.5 lb-N acre-1 and 13.9 lb-N acre-1, which were 48.9% and 66.9% lower than the annual NO3-N loss from fSfCfS and fCfSfC treatments. The average annual NO3-N loss of PP treatment was significantly lower than all corn-soybean treatments (p<0.05). Suction lysimeter NO3-N concentration Nitrate-nitrogen concentration in soil solution ranged from 0.1 to 33.4 mg N L-1 for fSfCfS, 0.4 to 38.1 mg N L-1 for fCfSfC, no detection (≤0.01 mg N L-1) to 26.6 mg N L-1 for rSrCrS, no detection to 22.1 for rCrSrC, no detection to 77.6 for kKkCkC, and no detection to 15.0 mg N L-1 for PP. ft Drainage and NO3-N leaching 2008 Integrated Crop Management Conference - Iowa State University — 279 On average over two depths, NO3-N concentration in the soil solution in 2007 for the rCrSrC treatment was found to be significantly lower than fCfSfC by 56.4% (p<0.05) (Table 7). Although not significant, NO3-N concentration in rSrCrS treatment was 21.5% lower than that in fSfCfS treatment. PP treatment significantly (p<0.05) reduced the NO3-N content in soil solution compared with any other treatments. ra these three months in 2006 were 34.3o, 53.1o and 60.4 oF which were higher than the long term average. However, in 2007, the average temperatures in March and May were 38.8 o and 64.6 o F which were higher than the average, but in April the average temperature was 45.3 oF, lower than the long-term average in April. The average temperatures in March, April, and May for 2008 were 29.5o, 43.9 o and 56.5 oF, which were lower than the long-term averages. NO3-N-nitrogen concentrations at 1-foot were not significantly different than those at 2-foot depth, indicating that NO3-N concentration was not stratified at these two depths. However, in the PP plots, the average NO3-N concentration in the soil solution at 1- and 2-foot was 1.2 mg N L-1, 72.9% lower than the flow-weighted NO3-N concentration in the tile line (3.5 feet deep). For the corn-soybean rotation treatments, no matter with or without rye as a winter cover, the NO3-N concentrations at 1- and 2-foot were generally higher than that in the tile flow in spring and early summer but lower in August and September. Moreover, in the corn-soybean and pasture treatment plots, the NO3-N concentration in the soil solution in April, May and June were lower than those in August and September. An inverse pattern was observed in kKkCkC treatment, which reflected the fertilizer application in June, 2007 and little uptake of N fertilizer due to poor corn growth. d 278 — 2008 Integrated Crop Management Conference - Iowa State University Biomass and N uptake of spring land covers Biomass and nitrogen uptake of spring land covers was lower in 2007 than in 2006 (Table 8 and Table 9). Winter rye cover crop growing in the rye-soybean treatment was chemically desiccated in the middle to late May and the rye in the rye-corn treatment was killed in the late April with a difference around 20 days. At killing, the average rye biomass was 1320 lb acre-1. The average biomass of rye followed by soybean was 2086 lb acre-1, while biomass of rye followed by corn was 553 lb acre-1. Within the 20 days after the rye followed by corn was killed, rye followed by soybean accumulated 79.8% of the biomass in 2006 and 77.9% of the biomass in 2007. In the early June, observed biomass was 3500 lb acre-1 for Kura clover and 2706 lb acre-1 for pasture. With the accumulation of above ground biomass, nitrogen content in the grass and legume shoot decreased during the sampling period from late March to early June. Nitrogen content declined ft This study evaluated the impacts of various land covers in NO3-N concentration and leaching in Iowa. In total, 51.4% of the annual rainfall exited through the subsurface drainage system. April, May and June were the main drainage months with 65.0% of the annual drainage. From the six different land cover treatments over two years, there were no significant differences among annual drainage volume. ra The average annual flow-weighted NO3-N concentration in the fallow corn or soybean treatments was 13.7 mg N L-1. NO3-N concentration in the drainage flow from the corn-soybean treatments during April, May and June consistently exceeded the 10 mg N L-1 limit set by USEPA for drinking water. Rye followed by soybean was found to significantly reduce annual flow-weighted NO3-N concentration for 2006. Reduction of monthly flow-weighted NO3-N concentration in April, May and June was observed in some months of 2006 and 2007. The average annual flowweighted NO3-N concentrations from the drain tile of the kKkCkC and PP treatments were 6.9 and 5.4 mg N L-1 respectively, and were significantly lower than other treatments. Compared with corn-soybean without spring land cover treatments, kura clover as a living mulch and perennial pasture treatments resulted in a 48.9% and 66.9% reduction in annual NO3-N leaching, respectively. Rye followed by soybean reduced the NO3-N concentration in the soil water solution significantly (56.4%) at the 1- and 2-foot depths. Pasture treatment showed significantly lower NO3-N concentrations in the soil solutions at these depths than all other treatments. At killing, the average nitrogen uptake by rye was 29.7 lb-N acre-1. In early June, the cumulative nitrogen uptake was 53.4 lb-N acre-1 for kura clover and 29.6 lb-N acre-1 for pasture. d Overall, this study indicates that winter rye cover crop, kura clover as a living mulch and perennial pasture land covers had positive effects on NO3-N concentration under the weather conditions presented during these three years in Iowa. References Baker, J.L. and H.P. Johnson. 1981. NO3-N-nitrogen in tile drainage as affected by fertilization. J. Environ. Qual. 4: 519-522. Baker, J.L., and S.W. Melvin. 1994. Chemical management, status, and findings. P.27-60. In Agricultural drainage well research and demonstration project—annual report and project summary. Iowa Dep.of Agric. And Land Stewardship, Des Moines. IA. Baker, J.L., K.L. Campbell, H.P. Johonson, and J.J. Hanway. 1975. NO3-N, phosphorus, and sulfate in subsurface drainage water. J. Environ. Qual. 4: 406-412. Baker, J.L., S.W. Melvin, D.W. Lemke, P.A. Lawlor, W.G. Crumpton, and M.J. Helmers. 2004. Subsurface drainage in Iowa and the water quality benefits and problem. Drainage VIII Proceedings of the Eighth International Symposium. ASAE Meeting Paper No. 701P0304. St. Joseph, MI. Cambardella, C.A., T.B. Moorman, D.B. Jaynes, T.B. Parkin, and D.L. Karlen. 1999. Water quality in Walnut Creek watershed: NO3-N nitrogen in soils, subsurface drainage water and shallow groundwater. J. Environ. Qual. 28:25-34. David, M.B., L.E. Gentry, D.A. Kovacic, and K.M. Smith. 1997. Nitrogen Balance in and Export from an Agricultural Watershed. J. Environ. Qual. 26: 1038-1048. Helmers, M. J., P. Lawlor, J. L. Baker, S. Melvin, D. Lemke. 2005. Temporal subsurface flow patterns form fifteen years in North-Central Iowa. ASAE Meeting Paper No. 05-2234. St. Joseph, MI. Kanwar, R.S., H.P. Johnson, J.L. Baker. 1983. Comparison of simulated and measured NO3-N loss in tile effluent. Transactions of the ASAE. 26(5): 1451-1457. ft Conclusion 2008 Integrated Crop Management Conference - Iowa State University — 281 Kaspar, T.C., D.B. Jaynes, T.B. Parkin, and T.B. Moorman. 2007. Rye cover crop and gamagrass strip effects on NO3-N concentration and load in tile drainage. Journal of Environmental Quality. 36:1503-1511. Kaspar, T.C., J.K. Radke, and J.M. Laflen. 2001. Small grain cover crops and wheel traffic effects on infiltration, runoff, and erosion. Journal of Soil and Water Conservation. 56:160-164. Lawlor, P.A., M.J. Helmers, J.L. Baker, S.W. Melvin, and D.W. Lemke. 2008. Nitrogen application rate effect on NO3-N-nitrogen concentration and loss in subsurface drainage for a cornsoybean rotation. Transactions of the ASABE. 51(1): 83-94. ra from 5.7% on March 29 to 1.9% on May 25 for the rye followed by soybean in 2007. At killing, the average nitrogen uptake by rye was 29.7 lb-N acre-1. In early June, the cumulative nitrogen uptake was 53.4 lb-N acre-1 for kura clover and 29.6 lb-N acre-1 for pasture. Lowrance, R. 1992. Nitrogen outputs from a field-size agricultural watershed. Journal of Environ. Qual. 21:602-607. Randall, G.W., and J.A. Vetsch. 2005. NO3-N losses in subsurface drainage from a corn-soybean rotation as affected by fall and spring application of nitrogen and nitrapyrin. J. Environ. Qual. 34: 590-597. Schilling, K.E. and Y.K. Zhang, 2004. Baseflow contribution toNO3-N-nitrogen export from a large, agricultural watershed, USA. Journal of Hydrology. 295: 305-316. Singh, R., M.J. Helmers, and Z. Qi. 2006. Calibration and validation of DRAINMOD to design subsurface drainage systems for Iowa’s tile landscapes. Agricultural Water Management. 85(2006)221-232. d 280 — 2008 Integrated Crop Management Conference - Iowa State University Strock, J.S., P.M. Porter, and M.P. Russelle. 2004. Cover cropping to reduce NO3-N loss through subsurface drainage in the northern U.S. Corn Belt. J. Environ. Qual. 33:1010-1016. Unger, P.W., and M.F. Vigil. 1998. Cover crop effects on soil water relationships. Journal of Soil and Water Conservation. 53: 200-207. Weed, D.A.J., and R.S. Kanwar. 1996. NO3-N and water present in and flowing from root-zone soil. J. Environ. Qual. 25: 709-719. 282 — 2008 Integrated Crop Management Conference - Iowa State University 2007 Sum mer Soybean Corn Soybean Corn K ura clover P asture Spring fallow fallow rye rye kura clover pasture 2008 Sum m er Corn Soybean Corn Soybean kura clove r+Corn Pasture Spring fallow fallow rye rye kura clo ver p astu re Su mm er So ybe an Co rn So ybe an Co rn ku ra clover+Co rn Pasture Table 2. Agronomic field activity timing. 2006 rye term in ation corn planting soyb ean P lanting fert ilizer applicat ion rye seeding 10-May - 2007 rye term in ation corn planting soyb ean P lanting fert ilizer applicat ion rye seeding 14-May 5-Ju n rye term in ation corn planting soyb ean P lanting fert ilizer applicat ion 23-May - 2008 fSfCfS - fCfSfC - rSrCrS 11-Oct rCrSrC 11-Oct kKkCkC - PP 4-M ay 18-M ay - 16-May 10-May 12-Oct 24-Ap r 4-M ay 18-M ay 12-Oct - - 17-M ay - 30-Apr 14-May 5-Ju n 25-Oct 23-M ay 17-M ay 25-Oct 14-May 5-Jun - 15-M ay 20-Jun 26-May 23-May - 6-M ay 15-M ay 20-Jun 15-May 20-Ju n - ft Managemen t rye seeding ra Year 2005 - Table 3. Average drainage volume, flow-weighted NO3-N concentration and NO3-N loss in 2006. Land cover treatments fSfCfS fCfSfC rSrCrS rCrSrC kKkCkC PP ---------------------------------------------------- Drainage inch -------------------------------------------------------April 2.6 a 2.8 a 2.8 a 1.8 a 2.6 a 3.2 a May 1.8 a 1.6 a 1.4 a 1.2 a 0.8 a 0.9 a July 0.5 a 0.3 a 0.4 a 0.8 a 0.2 a 0.1 a Annual 4.9 a 4.7 a 4.5 a 3.9 a 3.6 a 4.3 a -1 -------------------------------------- Flow weighted NO3-N concentration mg L ------------------------------April 14.4 a 11.9 a 13.0 ab 13.2 ab 7.0 c 8.4 bc May 16.3 ab 16.2 a 12.4 bc 13.4 ab 5.3 d 8.1 cd July 14.6 ab 10.2 a 9.6 b 21.1 ab 8.3 b 6.0 b d Month Annual flowweighted average 15.1 a 13.2 ab 12.6 b 14.8 a 6.7 c 8.2 bc ---------------------------------------------------- NO3-N loss lb-N acre-1----------------------------------------------April 8.5 a 7.5 a 8.2 a 5.5 a 4.1 a 6.1 a May 6.5 a 5.7 ab 4.0 abc 3.8 abc 1.0 c 1.7 c July 1.6 a 0.7 a 0.8 a 3.7 a 0.3 a 0.2 a Annual 16.6 a 14.0 ab 12.9 ab 12.9 ab 5.4 b 7.9 ab Means within a row followed by the same letter are not significantly different at p=0.05. Land cover treatments fSfCfS fCfSfC rSrCrS rCrSrC kKkCkC PP ------------------------------------------------------- Drainage inch -------------------------------------------------------------------------March 0.3 a 0.2 a 0.2 a 0.5 a 0.6 a 0.4 a April 4.6 a 3.7 a 5.2 a 4.4 a 5.6 a 4.4 a May 1.5 ab 1.5 ab 1.7 a 0.7 bc 0.4 c 1.2 abc June 0.4 a 0.1 a 0.2 a 0.1 a 0.1 a 0.2 a August 7.2 a 4.7 a 7.2 a 10.2 a 9.4 a 6.9 a Steptember 0.2 a 0.2 a 0.2 a 0.0 a 0.1 a 0.3 a October 5.1 a 4.7 a 6.8 a 6.9 a 4.9 a 3.9 a Annual 19.2 a 15.1 a 21.5 a 22.7 a 21.2 a 17.2 a -------------------------------------------- Flow weighted NO3-N concentration mg L-1 --------------------------------------------March 13.0 a 12.7 a 11.2 a 9.3 a 3.0 a 6.4 a April 14.3 a 13.2 ab 11.7 b 10.6 b 2.9 c 5.0 c May 16.1 a 16.0 a 13.1 b 12.7 b 3.1 c 4.6 c June 16.3 a 13.5 abc 13.1 ab 11.8 ab 3.9 c 4.9 bc August 12.3 a 12.9 a 9.6 a 8.9 a 11.1 a 5.2 b Steptember 11.4 a 10.5 a 7.5 a 5.8 a 5.8 a 3.3 a October 13.5 a 12.0 ab 12.9 a 9.2 b 5.8 c 3.9 c Annual flowweighted average 13.5 a 12.9 ab 11.5 ab 9.5 bc 7.2 cd 4.8 d ---------------------------------------------------------- NO3-N loss lb-N acre-1------------------------------------------------------------March 0.8 a 0.6 a 0.6 a 1.0 a 0.4 a 0.5 a April 15.1 a 11.1 ab 13.8 a 10.6 abc 3.7 c 4.9 bc May 5.4 a 5.5 a 5.1 a 1.9 b 0.3 b 1.2 b June 1.4 a 0.4 b 0.5 ab 0.2 b 0.1 b 0.2 b August 20.1 a 13.7 a 15.6 a 20.7 a 23.6 a 8.1 a Steptember 0.5 a 0.4 a 0.3 a 0.0 a 0.1 a 0.2 a October 15.5 ab 12.7 abc 19.8 a 14.3 ab 6.5 bc 3.5 c Annual total 58.7 a 44.3 ab 55.7 a 48.7 ab 34.8 ab 18.7 b Month ft 2006 ra Treatm ent No tatio n Sp rin g fSfCfS fallo w fCfSfC fallo w rSrCrS rye rCrSrC rye kKkCkC ku ra clover PP pasture Table 4. Average drainage volume, flow-weighted NO3-N concentration and NO3-N loss in 2007. Table 5. Drainage volume, flow-weighted nitrate concentration and nitrate loss in 2008 Land cover treatments fSfCfS PP fCfSfC rSrCrS rCrSrC kKkCkC ------------------------------------------------------- Drainage inch -------------------------------------------------------------------------April 3.8 a 3.3 a 3.8 a 5.1 a 4.8 a 5.5 a May 4.2 a 2.8 a 2.6 a 4.2 a 2.9 a 4.1 a June 9.0 a 7.0 a 6.8 a 10.1 a 9.3 a 8.7 a July 0.4 a 0.3 a 0.1 a 0.1 a 0.0 a 0.5 a Annual 17.3 a 13.4 a 13.3 a 19.5 a 17.0 a 18.8 a -------------------------------------------- Flow weighted NO3-N concentration mg L-1 --------------------------------------------April 13.2 a 13.8 a 13.1 a 11.5 a 7.7 b 4.9 b May 12.2 a 12.7 a 11.6 a 11.4 a 6.6 b 3.7 b June 11.5 a 12.6 a 12.1 a 11.4 a 5.8 b 2.5 c July 9.8 ab 12.4 a 11.3 a 10.8 a 6.8 b 2.5 c Month d Table 1. Land cover treatments. 2008 Integrated Crop Management Conference - Iowa State University — 283 Annual flowweighted 12.0 a 13.1 a 12.2 a 11.4 a 6.4 b 3.4 c ---------------------------------------------------------- NO3-N loss lb-N acre-1----------------------------------------------------------------April 9.7 a 10.3 a 10.7 a 12.7 a 8.3 a 5.7 a May 10.5 a 7.5 ab 5.9 ab 10.4 a 4.4 b 3.9 b June 23.4 a 21.1 a 18.3 ab 24.9 a 11.7 ab 5.4 b July 0.9 a 0.6 ab 0.2 ab 0.3 ab 0.1 b 0.2 ab Annual 44.6 a 39.6 ab 35.0 ab 48.3 a 24.6 bc 15.2 c 284 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 285 Table 6. Average annual drainage, flow-weighted NO3-N concentration and NO3-N loss in 2006, 2007, and 2008. Table 8. Biomass, nitrogen content and nitrogen uptake by rye, kura clover, and pasture in the spring of 2006. Land cover treatments kKkCkC fSfCfS fCfSfC PP rSrCrS rCrSrC ------------------------------------------------------- Drainage inch -----------------------------------------------------2006 4.9 a 4.7 a 4.5 a 3.9 a 3.6 a 4.3 a 2007 19.2 a 15.1 a 21.5 a 22.7 a 21.2 a 17.2 a 2008 17.3 a 13.4 a 13.3 a 19.5 a 17.0 a 18.8 a Average 13.8 a 11.0 a 13.1 a 15.4 a 13.9 a 13.4 a -1 ----------------------------------------- Flow weighted NO3-N concentration mg L ----------------------------2006 15.1 a 13.2 ab 12.6 b 14.8 ab 6.3 c 8.2 bc 2007 13.5 a 12.9 ab 11.5 ab 9.5 bc 7.2 cd 4.8 d 2008 12.0 a 13.1 a 12.2 a 11.4 a 6.4 b 3.4 c Average 13.6 a 13.7 a 12.1 a 12.2 a 6.9 b 5.4 b --------------------------------------------------- NO3-N loss lb-N acre-1------------------------------------------------2006 16.7 a 14.0 ab 12.9 ab 12.9 ab 5.2 b 7.9 ab 2007 58.7 a 44.3 ab 55.7 a 48.6 ab 34.8 ab 18.7 b 2008 44.6 a 39.6 ab 34.9 ab 48.3 a 24.6 bc 15.2 c Average 40.0 a 32.6 a 34.5 ab 37.0 a 21.5 bc 13.9 c Date Land Cover Treatments rSrCrS rCrSrC kKkCkC PP fSfCfS fCfSfC ---------------------------------------------------- 1-foot depth -------------------------------------------------April 21.4 25.1 14.8 10.7 8.5 May 12.2 15.2 13.0 7.5 2.3 1.1 June 8.7 16.6 17.7 4.1 2.9 5.0 July 13.6 17.9 11.0 8.3 August 5.0 2.0 2.8 3.9 24.9 0.2 September 16.0 6.7 7.5 5.6 23.2 0.0 [1] Average 12.8 13.9 11.1 6.6 12.4 1.6 --------------------------------------------------- 2-foot depth -------------------------------------------------April 19.8 30.8 7.3 19.3 1.0 May 17.6 26.6 11.7 12.2 2.8 0.2 June 15.3 27.6 10.1 4.7 2.0 2.1 July 13.4 21.4 10.0 4.6 0.6 August 4.2 8.2 4.1 3.2 22.4 0.6 September 8.7 7.1 12.4 4.5 38.3 0.1 [1] Average 13.2 20.3 9.2 8.1 13.2 0.8 Overall 13.0 ab 17.1 a 10.2 bc 7.4 c 12.8 b 1.2 d average [2] d Date [1]. Average over all observed value; [2]. Average over all monthly value. N content (%) rCrSrC rSrCrS 4.4 4.1 3.8 3.8 3.4 3.2 2.5 1.9 N uptake (lb N acre-1) rCrSrC rSrCrS 10.9 8.1 26.1 13.9 31.1 18.9 50.1 58.8 4/26/06 6/5/06 kKkCkC 1595 5525 kKkCkC 3.8 2.4 kKkCkC 33.1 75.9 PP 3.1 1.7 ft PP 1750 5169 PP 31.2 39.2 Table 9. Biomass, nitrogen content and nitrogen uptake by rye, kura clover, and pasture in the spring of 2007. -1 Date 3/29/07 4/5/07 4/13/07 4/19/07 4/27/07 4/30/07 5/10/07 5/17/07 5/25/07 Biomass (lb acre ) rCrSrC rSrCrS 49 50 56 85 64 86 100 89 176 211 332 294 617 0 974 0 1502 0 kKkCkC PP 863 160 1474 1849 N content (%) rCrSrC rSrCrS 5.7 6.0 4.8 5.0 5.1 5.2 4.5 4.9 4.3 4.5 3.3 3.4 2.9 2.3 1.9 kKkCkC PP 4.7 3.6 2.6 1.3 ra ra Table 7. NO3-N concentration in suction lysimeters at 1-foot and 2-foot depths in 2007. 4/12/06 4/19/06 4/26/06 5/10/06 5/17/06 Biomass (lb acre-1) rCrSrC rSrCrS 221 177 604 342 811 539 1760 2670 4/27/07 6/7/07 d ft Year -1 N uptake (lb N acre ) rCrSrC rSrCrS 3.2 3.3 3.0 4.8 3.7 5.1 5.1 4.9 8.4 10.6 12.2 11.3 19.8 24.4 31.8 kKkCkC PP 45.5 6.4 43.9 27.2 286 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 287 Tillage considerations on previously flooded soils H. Mark Hanna, Extension Ag Engineer, Agricultural and Biosystems Engineering, Iowa State University Temperature 30-year Mean Temperature 80 Introduction 60 Many Iowa fields had wet or underwater areas during part of the growing season. Many wet areas were planted late which resulted in late-maturing crop. Yields have been variable in these areas, sometimes significantly below that of yields in areas not subject to wet soil conditions. 4 3 ra Daily Precipitation (inch) Precipitation During fall 1993, four farmer cooperators on five different sites in the Henry-Des Moines-Louisa county area in southeast Iowa agreed to establish replicated strips of tillage trials in production corn-soybean fields to be planted in spring 1994 (Table 1). According to rainfall records at nearby weather recording stations, the fields had received 66 – 85% above normal rainfall during the April – October 1993 growing season. 1 5/1/06 9/1/06 1/1/07 5/1/07 Date d Field study 2 0 1/1/06 Figure 1. Daily temperature and precipitation: 2006-2008. Similar concerns after the 1993 crop season prompted a field study with farmer cooperators to compare tillage effects on soil conditions and crop yield during the following 1994 crop season. Although 1993’s excessive rainfall events occurred more during mid-season (June-July-August) rather than 2008 (excessive rain during April-May-June), in both cases significant tillage was not able to be done during the growing season in most instances. ra 0 In these conditions a frequent concern of growers is that excessive rainfall, wet soil, and/or lower crop yield have damaged soil structure and that these damages may warrant significant tillage operations prior to next season’s crop to loosen soil and ameliorate damage to soil structure. 9/1/07 1/1/08 5/1/08 Table 1. County, soil type, and crop of farmer cooperator sites Site County Soil type Crop Henry Mahaska/Taintor silty clay loam Corn 2 Des Moines Mahaska/Taintor silty clay loam Corn 3 Henry Kalona silty clay loam Soybean 4 Louisa Mahaska/Otley silty clay loam Corn 5 Louisa Mahaska/Otley silty clay loam Soybean 1 d 20 ft 40 ft Average Daily Temperature (F) 100 Each grower compared three tillage management schemes during fall field preparation for the subsequent crop: 1) deep tillage using a subsoiler (ripper) to a depth of approximately 12 in., 2) moderate tillage with a chisel plow or disk operating at a depth of 6 – 7 in., or 3) no fall tillage. During the spring prior to planting both the subsoiled and chiseled or disked ground was field cultivated to level the soil for planting. A field cultivator was also used at a very shallow (2 in.) depth by some of the operators in previously untilled soil areas as they were concerned about their planter’s ability to function in an unprepared seedbed. This resulted in a comparison of three tillage treatments (‘shallow’, ‘moderate’, and ‘deep’). 288 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 289 Effects on both soil compaction and crop yield were measured during the 1994 growing season. Soil compaction measurements included soil sampling in April prior to planting (and prior to tillage in the shallow treatment), in mid-June as crop vegetative growth was accelerating, and post-harvest in October. Other natural factors such as over-winter freeze-thaw cycles in the soil prior to the April measurement or effects of shrink cracks propagating as soil moisture was used during the crop season prior to the October measurement may have done as much or more than tillage to loosen the soil. Results and discussion Penetrometer resistance was, however, statistically less with tillage before planting in April (Figure 2). Just after harvest, penetration resistance for shallow and moderate tillage was similar, but both were greater than that of deep tillage. a. Pre-plant Penetrometer, psi 0 1 1.1 1.2 0 2 6 8 10 12 ra Depth, in. 4 1.3 1.4 1.5 1 1.1 1.2 1.3 Shallow Moderate Deep 8 12 140 160 180 200 b. Post-harvest Penetrometer, psi 0 0 1.4 1.5 50 100 d 2 150 200 250 300 350 400 450 500 4 4 Shallow Moderate Deep Depth, in. d 120 Shallow Moderate Deep 10 2 Depth, in. 100 6 0 6 80 4 Bulk density, g/cc 0.9 60 2 b. Post-harvest 0.8 40 ft 0.9 20 0 Depth, in. Bulk density, g/cc 0.8 ft a. Pre-plant ra Fall tillage after the wet soil conditions did not have a statistically significant effect on the resulting soil bulk density, either as measured during pre-plant conditions in April or postharvest conditions in October (Figure 1). 6 Shallow Moderate Deep 8 8 10 10 12 12 Figure 1. Average pre-plant and post-harvest soil bulk density from field-scale plots receiving shallow, moderate, or deep tillage. Figure 2. Average pre-plant and post-harvest penetrometer resistance from field-scale plots receiving shallow, moderate, or deep tillage. A rainfall event during mid-June soil sampling after soil measurements had been taken at two of the sites precluded sampling at other locations as crops were rapidly developing. Data not shown from these post-plant measurements at these two sites agreed with pre-plant and postharvest measurements. Bulk density was not different among tillage systems and although penetration resistance was less in deep tilled soil, there was no difference in penetration resistance by this time of rapidly developing root systems between shallow and moderate tillage. ft Yield was unaffected by tillage (Table 2) in the year after extremely wet or ponded soil conditions. Growing conditions were relatively good despite rainfall during the crop season that was only about 2/3 that of a normal year. Soil conditions were dry at harvest as evidenced by high penetrometer readings (Figure 2b). water on silty clay loam textured fields in southeast Iowa: • As measured by soil bulk density (the mass of soil particles within a given volume) tillage did not physically loosen soil any more than soil that was left untilled. • Tillage lessened penetration resistance the spring after fall tillage, but the effect did not linger into the growing season unless tillage was deep (~12 in.). • Crop yield was unaffected the next year by the depth or amount of tillage that was done. Because there was no increase of crop yield with tillage (in fact a slight decrease), growers should carefully consider the amount of extra yield required to cover tillage costs and whether benefits exist for tilling soil after a season of significant rainfall. Tillage was counter-productive and lowered profit potential in this study. Table 2. Average crop yields for shallow, moderate, and deep tillage after ‘rain-compacted’ soil. Reference Shallow Deep Soybean 204 60 193 59 197 56 NS[a] NS ra Moderate Corn Least significant difference Yields were not statistically different [a] Although there was some difference in penetrometer readings between tillage systems, crop root growth is typically not inhibited below 300 psi as was measured during April and June. High post-harvest penetrometer readings were likely due to dry soil conditions rather than a sign of late-season rooting difficulty. d Tillage generally had a limited effect in loosening soil. Because yields were equivalent if not higher with reduced tillage, input costs for extra tillage passes decreased the potential for profitability. Current custom rates for subsoiling and chisel plowing are in the range of $15 - $20 and $10 - $15 per acre, respectively. Costs with owned equipment are often similar to custom costs unless equipment is well depreciated. Results observed in this study may not be unusual. Some growers worry about the weight of standing, ponded water on soil. Although there is a certain amount of pressure associated with increasing depth of standing water, the pressure is hydrostatic and exerted equally in all directions (i.e., both ‘up’ and ‘down’) so that soil voids are not compacted by water weight. Caution should always be used when attempting to extrapolate results to different situations (e.g., rainfall patterns during the prior year, different soil and weather growing conditions during the subsequent crop season), but these results suggest being cautious before spending time, fuel, and money tilling to ameliorate poor, wet soil growing conditions from a prior season. Conclusions Based on these results following fall primary tillage after a year of excessive rainfall and standing Heikens, K.E., D.L. Karlen, D.C. Erbach, H.M. Hanna, and J.H. Jensen. 1999. Tillage effects on previously flooded soils. Journal of Production Agriculture 12(3):409-414. ra Tillage d Yield, bu/acre 2008 Integrated Crop Management Conference - Iowa State University — 291 ft 290 — 2008 Integrated Crop Management Conference - Iowa State University 292 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 293 Tillage and crop rotation management impact on yield and soil quality Mahdi Al-Kaisi, Associate Professor, Agronomy, Iowa state University ft Tillage decision is only one concern farmers have to make every fall. There are many other factors need to be considered in selecting a tillage system for any given field or region within the state. Those factors are soil conditions, which can include, soil slope, soil drainage, topsoil depth or the A-horizon depth. Other factors need to be considered, which are equally important such as hybrid selection, crop rotation, and management factors, such as, residue cover, type of residue (corn or soybean), soil moisture condition at the time of making the decision, timing of tillage operation, fertilizer management in conjunction with tillage operation, type of residue management equipment, planting and harvesting equipment, compliance with conservation plans, and above all, is the economic return and benefits of selecting any tillage system. ra The variability in soil conditions will be a key factor in selecting a tillage system that will influence crop response and ultimately yield expectations. However, crop response to tillage systems has been demonstrated to be different for the same tillage system in a different part of the state or different regions elsewhere. Different tillage systems affect soil temperature, soil moisture conditions, soil compaction, soil productivity, and nitrogen movement and N availability differently. These effects will be indicated in crop response to different tillage systems, where soil temperature plays a significant role in early seed germination, organic N mineralization, nutrient and residue incorporation, and weed and pest control. Understanding site specific effect of tillage can help significantly reducing input cost and reduce the negative impact on water, air, and soil quality. Conservation tillage systems continue to be a very important component of a crop production system in terms of economic return and environmental benefits. However, the challenges in managing such systems, and namely no-tillage, are related to the proper management practices, such as the availability of drainage in poorly drained soils, use of residue management residue attachments, seeding depth, and fertilizer management. Also, the timing of conducting field operations, N application, manure injection, etc., has to be done when soil moisture condition is below field capacity to avoid serious soil compaction problems. d d ra ft Introduction Soil moisture and soil temperature conditions in the seedbed zone (top 2-6 inches) can promote or delay seed germination and plant emergence (Kaspar et al., 1990; Schneider and Gupta, 1985). Therefore, healthy plant growth and development require soil conditions that have adequate soil moisture and minimal root penetration resistance (Phillips and Kirkham, 1962). Soil temperature can be affected by surface residue cover, causing cooler surface soil temperature and slower soil drying in the spring (Fortin, 1993; Kaspar et al., 1990) in spite of reducing soil erosion and surface runoff (Cruse et al., 2001). Removal of residue from the row can reduce inrow soil moisture content in the seedbed, while conserving interrow soil moisture. Unlike soil moisture, soil temperature has an inverse relationship with the amount of residue cover. Tillage systems have a significant effect on N dynamics by affecting N pools in the soil system. Soil disturbance during the tillage process and the incorporation of surface residue increases soil aeration, which can increase the rate of residue decomposition (McCarthy et al., 1995). 294 — 2008 Integrated Crop Management Conference - Iowa State University This process impacts soil organic N mineralization whereby readily available N for plant use is increased (Dinnes et al., 2002). The type of tillage system can influence the amount of N available for loss in the soil profile. Deep accumulation of NO3-N in the soil profile represents a potential for NO3-N leaching into shallow water tables (Keeney and Follett, 1991). • Input costs account for machinery costs, labor, seed, nutrients, chemicals, and insurance. Input cost does not include land rental ($190 cash rent equivalent). • Labor was figured at $11.00/hr, nutrients are based on crop removal rates, and insecticides were accounted for in corn after corn. • Herbicide tolerant soybeans were used in input costs considerations. Results and discussion • Input costs based from ISU Extension publication FM 1712 and Ag Decision Maker file A120. d In a more recent tillage study from eight locations across Iowa, no-tillage corn and soybean yields generally were not significantly different at Crawfordsville and Kanawha (Tables 2 through 5). This is encouraging for producers who are reluctant to switch to no-tillage due to concerns of poor crop performance. An effective no-tillage system depends on properly selecting and setting up the planter, adequate fertility program, and efficient drainage system especially in poorly drained soils. The success of any conservation system depends heavily on how the system is managed. Generally, conservation systems require less input costs. The advantage of conservation systems is in the fuel saving, where no-tillage generally requires one gal per acre compared to 4.1 gal per acre for conventional tillage operations. The reduction in the number of implements and horsepower needed is also a significant savings in capital and maintenance costs. Fewer trips across the field reduce the fuel and labor needed. Table 1. Total production input costs per acre for different tillage systems for corn and soybean under different crop rotations. Corn after Soybean ($/acre) Corn After Corn ($/acre) Soybean After Corn ($/acre) No-tillage 348 392 186 Strip tillage 355 399 193 Chisel Plow 366 411 196 Deep Rip 372 417 202 Moldboard Plow 366 415 201 Table 2. Corn and soybean yields under a corn-soybean rotation at the ISU Crawfordsville Research Farm. Yields are corrected to 15.5 and 13.0% for corn and soybean respectively. 2003 2004 Soybean (c/S) ft Corn (C/s) 2005 2006 2007 2003 2004 2005 2006 2007 - - - - - - - - - - - - - - - - - - - - - - -bushels / acre- - - - - - - - - - - - - - - - - - - - - - - No-Tillage 212.8 180.0 171.3 189.1 159.3 38.7 55.1 71.8 56.8 59.4 Strip-Tillage 205.9 190.7 168.3 182.1 161.1 39.5 55.9 69.8 55.1 58.9 Deep Rip 209.7 200.2 171.0 185.7 170.8 42.2 57.7 70.2 56.0 59.6 Chisel Plow 211.6 207.9 177.4 184.6 168.8 40.6 55.7 69.5 58.5 57.5 ra ra ft A long-term study comparing different tillage and crop rotation systems across Iowa showed that no-tillage corn and soybean yields were competitive with moldboard plowing, deep-rip, chisel plowing, and ridge tillage for more than 8 years after no-tillage was established (Al-Kaisi and Yin, 2004; Yin and Al-Kaisi, 2004). No-tillage typically yielded 5 percent less, especially in poorly drained areas compared to other tillage systems. However, the economic return of different tillage systems showed no-tillage had an advantage over other tillage systems due to the lower input cost associated with no-tillage (Table 1) (Al-Kaisi and Yin, 2004; Yin and Al-Kaisi, 2004). On average, No-tillage system reduced input cost for corn production by approximately $18/acre under corn-soybean rotation and $18.50/acre for corn following corn compared to all conventional tillage systems (Table 1). These input costs in Table 1 did not include the land cost and they may vary from one farm to another based on level of management and other additional inputs. No-tillage shows saving in input cost for soybean production of $12/acre compared to conventional tillage systems as well. At the mean time, conventional tillage systems show no advantages in soybean yield over no-tillage across the state (Tables 2-5). Moldboard Plow LSD(0.05) a 5-Tillage Average 202.7 214.1 179.2 209.3 185.9 41.7 58.3 69.8 64.6 60.1 16.1 22.8 13.9 25 14.8 3.2 3.3 5.4 4.2 3.5 208.5 198.6 173.4 190.2 169.2 40.5 56.5 70.2 58.2 59.1 Least significant differences (LSD(0.05)) are based on a Fisher test. Yield differences greater than the least significant difference are significantly different. a Table 3. Yields are corrected to 15.5 and 13.0% for corn and soybean respectively. Corn (C-c-s) 2005 d Productivity and profitability Tillage System 2008 Integrated Crop Management Conference - Iowa State University — 295 Corn (c-C-s) 2003 2006 Soybean (c-c-S) 2004 2007 - - - - - - - - - - - - - - - -bushels / acre- - - - - - - - - - - - - - - - No-Tillage 165.6 129.8 208.3 57.6 64.1 Strip-Tillage 158.8 149.2 205.4 59.7 64.0 Deep Rip 163.9 146.1 201.0 60.0 62.7 Chisel Plow 163.3 157.7 196.4 59.8 60.2 Moldboard Plow 164.3 149.4 218.4 58.8 63.2 8.6 25.6 10.6 2.6 2.6 146.4 205.9 59.2 62.8 LSD(0.05) a 5-Tillage Average 163.2 Least significant differences (LSD(0.05)) are based on a Fisher test. Yield differences greater than the least significant difference are significantly different. a 296 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 297 Table 4. Corn and soybean yields under a corn-soybean rotation at the ISU Kanawha Research Farm. Yields are corrected to 15.5 and 13.0% for corn and soybean respectively. Corn (C/s) 2003 2004 2005 2006 Soybean (c/S) 2003 2004 2005 2006 2007 187.7 172.4 136.6 189.1 38.2 56.5 54.6 63.2 56.1 Strip-Tillage 191.7 181.1 146.0 188.2 38.0 57.8 54.1 59.9 56.3 Deep Rip 190.7 188.8 181.3 191.1 39.4 57.1 53.1 57.9 58.8 Chisel Plow 198.3 192.2 189.2 190.9 39.9 56.8 52.2 59.7 56.5 Moldboard Plow 196.7 191.2 188.5 196.0 40.7 57.8 53.5 57.4 56.7 LSD(0.05) 32.2 11.2 24.7 9.3 3.7 4.4 3.5 3.4 8.4 5-Tillage Average 193.0 185.1 168.3 191.1 39.2 57.2 53.5 59.6 56.88 a ft No-Tillage ft - - - - - - - - - - - - - - - - - - - -bushels / acre- - - - - - - - - - - - - - - - - - - - Least significant differences (LSD(0.05)) are based on a Fisher test. Yield differences greater than the least significant difference are significantly different. a 2004 Corn (c-C-s) 2005 Soybean (c-c-S) 2003 2006 - - - - - - - - - - - - - - - - - -bushels / acre- - - - - - - - - - - - - - - - - - No-Tillage 174.1 172.8 214.0 37.4 63.4 Strip-Tillage 192.3 177.7 220.1 34.9 53.4 Deep Rip 188.5 196.8 223.2 38.9 59.4 Chisel Plow 198.6 221.9 218.3 37.5 60.5 Moldboard Plow 200.9 208.3 232.0 39.3 60.3 LSD(0.05)a 14.5 47.2 9.7 2.4 12 5-Tillage Average 190.9 191.94 221.5 37.6 59.4 d a 2007 Least significant differences (LSD(0.05)) are based on a Fisher test. Yield differences greater than the least significant Tillage effect on soil quality • Carbon storage: Intensive tillage operations can have negative effect on soil organic carbon by oxidizing organic matter. Results from tillage studies in Iowa shows consistent decline in organic carbon with increase intensity in tillage operations (Fig. 1). Aerating soil increases the rate of soil organic matter decomposition and emission of carbon dioxide. Soil carbon is beneficial to improve soil structure and nutrient and water holding capacity. ra Corn (C-c-s) Figure 1. Soil carbon as affected by tillage and crop rotation at the top 6 inches for two sites from 2002 to 2004. • Erosion and water quality: Surface residues from both corn and soybean provide protection from both wind and water erosion. Cover crops following soybean and corn silage harvest can be used to increase the amount of residue cover and stabilize the surface soil. Additionally, waterways, terraces, and buffer strips provide living protection that controls the flow of surface water runoff and allow for sediments and nutrients to settle out before leaving the field. d ra Table 5. Corn and soybean yields under a corn-corn-soybean rotation at the ISU Kanawha Research Farm. Yields are corrected to 15.5 and 13.0% for corn and soybean respectively. • Crop residue: The more intensive a tillage pass is, the more residue will be broken down and buried. Crop residue is important to hold surface soil in place and protect the soil surface from raindrop and wind impacts. Crop residue also helps hold snowfall in place, which in the spring will contribute to subsurface soil moisture. • Soil structure: Tillage operations break soil aggregates and decrease pore spaces that are responsible for enhancing water infiltration. By switching to conservation tillage and using cover crops the soil will build better soil structure due to less soil disturbance and increased soil organic matter. • Soil compaction: There is a misconception of increased soil compaction with conservation systems. Research shows, fields under conservation systems have much better developed soil structure and pore spaces than conventional systems. The improved soil structure provides soil the strength to withstand heavy field equipment load. Al-Kaisi, M.M. 2005. Conservation systems role in sustaining soil productivity and soil quality. Presentation at the Integrated Crop Management conference, Ames, IA. 1 Nov 2005. ft Al-Kaisi, M.M., and X. Yin. 2004. Stepwise time response corn yield and economic return to no tillage. Soil Till. Res. 78: 91-101. Cruse, R.M., R. Mier, and C.W. Mize. 2001. Surface residue effects on erosion of thawing soils. Soil Sci. Soc. Am. J. 65: 178-184. Dinnes, D.L., D.L. Karlen, D.B. Janes, T.C. Kasper, J.L. Hatfield, T.S. Colvin, and C.A. Cambardella. 2002. Nitrogen management strategies to reduce nitrate leaching in tiledrained Midwest soils. Agron. J. 94:153-171. ra Fortin, M.C. 1993. Soil temperature, soil water, and no-till corn development following in-row residue removal. Agron. J. 85:571-171. Kasper, T.C., D.C. Erbach, and R.M. Cruse. 1990. Corn response to seed-row residue removal. Soil Sci. Am. J. 54:1112-1117. Keeney, D.R., and R.F. Follett. 1991. Overview and introduction, p. 9-17, In R. F. Follett, et al., eds. Managing nitrogen for groundwater quality and farm profitability. SSSA, Inc., Madison, WI. McCarthy, G.W., J.J. Meisinger, and F.M.M. Jenniskens. 1995. Relationship between total-N, biomass-N and active-N under different tillage systems and N fertilizer treatments. Soil Biol. Biochem. 27:1245-1250. d Phillips, R.E., and D. Kirkham. 1962. Soil compaction in the field and corn growth. 54:29-34. Schneider, E.C., and S.C. Gupta. 1985. Corn emergence as influenced by soil temprature, metric potential, and aggregate size distribution. Soil Sci. Soc. Am. J. 49:415-422. Yin, X., and M.M. Al-Kaisi. 2004. Periodic response of soybean yields and economic returns to long-term no-tillage. Agron. J. 96:723-733. J. 49:415-422. Using GIS technology for Iowa pesticide distribution and transport modeling Joost Korpel and Cam Conrad, Iowa Geological Survey, Iowa Department of Natural Resources Kristine Schaefer and Rich Pope, Extension Program Specialists, Iowa State University The patterns of pesticide occurrence in surface and ground waters are linked to agricultural practices and the product’s susceptibility to leaching and runoff. Pesticide use information has historically been catalogued in relation to points of sale from agrichemical dealerships. In an effort to provide a wide audience with an understanding of these occurrences and patterns, an atlas was developed during 2006 that provided a web-based front end to the data. The atlas links pesticide calculations of pounds of active ingredients sold with geographic information and water monitoring data using Geographic Information System (GIS) software. ft References 2008 Integrated Crop Management Conference - Iowa State University — 299 Pesticide transport is also being studied through computer modeling in Iowa, Kansas, Missouri, and Nebraska. The work uses a GIS-based pesticide “favorability” model that uses soil characteristics to predict where pesticides will create the least amount of potential environmental impact based on leaching, runoff, and particle-adsorbed runoff potential. ra • Soil moisture: A major benefits of conservation systems is the enhancement of subsurface soil moisture due to improvement of soil organic matter and water holding capacity. This is critical in areas where precipitation is limited and conservation of soil moisture is a priority. Iowa established the Iowa Pesticide Sales Database in the 1987 Groundwater Protection Act. The database is an ongoing collection of data on pesticide sales that are submitted from licensed dealers as a requirement of licensure. From these sales data, trends in pesticide use can be tracked by region through the years, which coupled with water monitoring data, allow for targeted educational programming. At least three pesticide use or distribution data sources exist, namely the Iowa Pesticide Sales Database, Iowa Geologic Survey database (IAPEST) on water contaminants in Iowa, and a recently conducted pesticide use survey conducted by ISU Extension. From these data sources it is possible to generate graphics to illustrate trends and use patterns as summaries that will be shared with the originating agencies and prepared for dissemination to the public. d 298 — 2008 Integrated Crop Management Conference - Iowa State University 300 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 301 Soils 101: How to apply the information in the Clay County Soil Survey for Northwest Iowa farmers and ag-professionals. ft The Soil Survey of Clay County, Iowa is a publication of the National Cooperative Soil Survey. Major field work was completed in 1999. Soil names and descriptions were approved in 2002. The survey was made cooperatively by the Natural Resources Conservation Service; the Iowa Agriculture and Home Economics Experiment Station and the Cooperative Extension Service, Iowa State University; the division of Soil Conservation, Iowa Department of Agriculture and Land Stewardship; and the Clay County Conference Board. ra Soil survey information has many useful purposes, including such diverse items as suitability for building site development, wildlife habitat selection, and selection of construction materials. Differences in crop production and crop suitability can also be explained by soil survey information. Agronomists who work with production agriculture can use the information in the soil survey report for many purposes. Some scenarios and possible soil survey report information are listed below. Possible Scenarios Reference tables are available for Troubleshooting crop yields Corn Suitability Rating, subsoil nutrients Suitability for alfalfa alfalfa yields, water table Subsoil soil fertility levels subsoil P, subsoil K Troubleshooting problem fields clay content, water holding capacity Drainage problems subsoil clay content A production agronomist might be asked to troubleshoot low corn or soybean yields in a field. For example, Wadena, Webster and Collinwood soils would appear in a similar position on the landscape and could be described by a casual observer as ‘good black soil’. Furthermore, these soils could be present in the same field. However, major differences in the subsoil will affect crop production. The Wadena soil has mostly gravel in the subsoil (clay content 1-5% 26 to 80 inches deep). Webster soils have clay loam in the subsoil (clay content 12-22% 32-60 inches deep). Collinwood soils are formed in old lakebeds and have a high clay content in the subsoil (clay content 34-60% 15-33 inches deep). Corn Suitability Ratings (CSR) are therefore very different for these three soils. The Webster soil has an ideal amount of clay in the subsoil and has a CSR of 77. The Wadena soil has a CSR of 52 since the low subsoil clay content does not retain moisture during dry summer months. Conversely, the Collinwood soil has a CSR of 67 because the excessive clay in the subsoil restricts root growth. The example of the Wadena soil is likely fairly obvious to anyone involved in production agriculture. Water holding capacity is listed for each soil mapping unit for the topsoil and subsoil. The information on water holding capacity further explains the differences in crop productivity between a Wadena, Webster and a Collinwood soil. d d ra ft Paul Kassel, Extension Field Agronomist, Iowa State University 302 — 2008 Integrated Crop Management Conference - Iowa State University 2008 Integrated Crop Management Conference - Iowa State University — 303 Information in the soil survey report can be useful for selecting fields for different crops. For example, the expected corn and soybean yields from a Webster soil and a Clarion soil (SMS 138) would be similar. However, the alfalfa yield from a Clarion soil would be reported as 5.5 ton per acre versus 3.9 ton per acre for the Webster soil. Past experience would likely confirm these production figures. However, the soil survey would give some explanation as to the cause. The seasonal high water table for a Webster soil is listed as 0 to 1.0 foot deep during the early growing season. Clarion soils would have a high water table listed as 4.0 to 6.0 foot deep for most of the growing season. References National Cooperative Soil Survey et al. 2002. Soil Survey of Clay County, Iowa. ra d The Sac-Ransom-Rushmore soils were mapped in Clay County. The Sac-Ransom-Rushmore soils have 20-40 inches of loess over till. Everly-Wilmonton-Letri soils were also mapped in Clay County. The Everly-Wilmonton-Letri soils have characteristics of loess and erosional sediments over glacial till. The Everly-Wilmonton-Letri would be somewhat similar to the Kenyon-ClydeFloyd soils in northeast Iowa. Everly soils were mapped in the previous soil survey report. However, the Wilmonton series replaced Nicollet clay loam (soil map symbol Nc), and the Letri series replaced Tripoli (soil map symbol Tr). d ra Galva-Primghar-Marcus soils were the predominant soils in the western part of the county as reported in the previous soil survey report. The current soil survey report further delineates some soil properties and replaced those soil mapping units. The Galva-Primghar-Marcus soils have over 60 inches of loess over glacial till. The current soil survey actually found that there were very few areas in the county that had more than 60 inches of loess. Therefore, the Annieville, McCreath and Gillett Grove soil mapping units were created. The AnnievilleMcCreath-Gillett Grove soils have 40-60 inches of loess over glacial till. ft ft Clay County has three major soil associations; Galva-Primghar, Everly-Wilmonton-Letri, and Clarion-Nicollet-Webster associations. There are several minor associations in Clay County. One of these is the Wilmonton-Ransom-Afton association which occupies 20 percent of the county. Another association is the Clarion-Nicollet-Webster association which occupies 25 percent of the county.
