Why conduct experiments?...
 To explore new technologies, new crops, and
new areas of production
 To develop a basic understanding of the factors
that control production
 To develop new technologies that are superior
to existing technologies
 To study the effect of changes in the factors of
production and to identify optimal levels
 To demonstrate new knowledge to growers and
get feedback from end-users about the
acceptability of new technologies
What is a designed experiment?
 Treatments are imposed (manipulated) by
investigator using standard protocols
 May infer that the response was due to the
treatments
Potential pitfalls
 As we artificially manipulate nature, results may not
generalize to real life situations
 As we increase the spatial and temporal scale of
experiments (to make them more realistic), it becomes
more difficult to adhere to principles of good
experimental design
What is an observational study?
 Treatments are defined on the basis of existing
groups or circumstances
 Uses
– Early stages of study – developing hypotheses
– Scale of study is too large to artificially apply treatments
(e.g. ecosystems)
– Application of treatments of interest is not ethical
 May determine associations between treatments and
responses, but cannot assume that there is a cause
and effect relationship between them
 Testing predictions in new settings may further
support our model, but inference will never be as
strong as for a designed (manipulative) experiment
Some Types of Field Experiments
(Oriented toward Applied Research)
 Agronomy Trials
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Fertilizer studies
Time, rate and density of planting
Tillage studies
Factors are often interactive so it is good to include
combinations of multiple levels of two or more factors
– Plot size is larger due to machinery and border effects
 Integrated Pest Management
– Weeds, diseases, insects, nematodes, slugs
– Complex interactions betweens pests and host plants
– Mobility and short generation time of pests often create
challenges in measuring treatment response
Types of Field Experiments (Continued)
 Plant Breeding Trials
– Often include a large number of treatments (genotypes)
– Initial assessments may be subjective or qualitative using
small plots
– Replicated yield trials with check varieties including a long
term check to measure progress
 Pasture Experiments
– Initially you can use clipping to simulate grazing
– Ultimately, response measured by grazing animals so plots
must be large
– The pasture, not the animal, is the experimental unit
Types of Field Experiments (Continued)
 Experiments with Perennial Crops
– Same crop on same plot for two or more years
– Effects of treatments may accumulate
– Treatments cannot be randomly assigned each year so it is not
possible to use years as a replication
– Large plots will permit the introduction of new treatments
 Intercropping Experiments
– Two or more crops are grown together for a significant part of the
growing season to increase total yield and/or yield stability
– Treatments must include crops by themselves as well as several
intercrop combinations
– Several ratios and planting configurations are used so number of
treatments may be large
– Must be conducted for several years to assess stability of system
Types of Field Experiments
(Continued)
 Rotation Experiments
– Determine effects of cropping sequence on target crop, pest or
pathogen, or environmental quality
– Treatments are applied over multiple cropping seasons or years,
but impact is determined in the final season
 Farming Systems Research
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To move new agricultural technologies to the farm
A number of farms in the target area are identified
Often two large plots are laid out - old versus new
Should be located close enough for side by side comparisons
May include “best bet” combinations of several new technologies
Recent emphasis on farmer participation in both development
and assessment of new technologies
Choice of Experimental Site
 Site should be representative
 Grower fields may be better suited to applied research
 Suit the experiment to the characteristics of the site
– make a sketch map of the site including differences in
topography
– minimize the effect of the site sources of variability
– consider previous crop history
– if the site will be used for several years and if resources
are available, a uniformity test may be useful
Greenhouse effects
 Greenhouse and growth chambers are highly
controlled, but in practice may be quite variable
 Not representative of field conditions
– light
– growth media
– unique insect pests and diseases
 Experiments can be conducted in the off-season
Experimental Error
Variation between plots treated alike is always present
 Modern experimental design should:
 provide a measure of experimental error variance
 reduce experimental error as much as possible
Natural sources of error in field experiments
 Plant variability
– type of plant, larger variation among larger plants
– competition, variation among closely spaced plants is smaller
– plot to plot variation because of plot location (border effects)
 Seasonal variability
– climatic differences from year to year
– rodent, insect, and disease damage varies
– conduct tests for several years before drawing firm conclusions
 Soil variability
– differences in texture, depth, moisture-holding capacity, drainage,
available nutrients
– since these differences persist from year to year, the pattern of
variability can be mapped with a uniformity trial
Uniformity Trials
 The area is planted
uniformly to a single crop
 The trial is partitioned into
small units and harvested
individually
 Adjustments are made to
distinguish patterns in the
data from random noise
 Areas of equal yield are
delineated
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Interpretation
 Determine suitability of the site
for the experiment
– uniformity critical for fertility trials
 Make decisions concerning
management of site over time
– cover crops
 Group plots into blocks to
reduce error variance within
blocks
– blocks do not have to be
rectangular
 Determine size, shape and
orientation of the plots
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Uniformity trials?
 costs
 time constraints
 land limitations
 pressure to publish or perish
 may already have knowledge of field
characteristics, previous cropping history
 new technological tools may achieve the same
or better result
Precision Agriculture
Techniques, technologies, and management strategies that
address within-field variability of parameters that affect crop
growth.
soil type
soil organic matter
plant nutrient levels
topography
water availability
weeds
insects
Tools of Precision Agriculture
 GPS and GIS – constant reference to
geographic coordinates
 Remote Sensing – infrared maps
 Equipment such as combines that can
continuously monitor yield at harvest
 Crop Modeling
 Spatial analyses
Example: central Missouri farm
Aerial photograph, soil pH and 3-year average grain yields
Source: http://muextension.missouri.edu/explore/envqual/wq0450.htm
Spatial Analyses
 Utilize patterns in the data to adjust for heterogeneity in
an experiment
 Example: ASReml
http://www.vsni.co.uk/software/asreml
Not a substitute for good experimental design and technique!