2007
Southeast Dairy Herd
Management Conference
November 6 & 7, 2007
Georgia Farm Bureau Building
Macon, Georgia
- Sponsors Cooperative Extension Service
Auburn University
Clemson University
University of Florida
University of Georgia
Southeast Dairy Herd
Management Conference
PROCEEDINGS
Editor
Dr. Lane O. Ely
Department of Animal and Dairy Science
Rhodes Center for Animal and Dairy Science
The University of Georgia
Athens, GA 30602-2771
Editorial Assistant
Jennifer Oates
Department of Animal and Dairy Science
Rhodes Center for Animal and Dairy Science
The University of Georgia
Athens, GA 30602-2771
Permission to reprint material is granted, provided the meaning is not changed. Credit
given to the author and publication as source material will be appreciated.
Product names in this publication are used for the sake of clarity and in no way imply
endorsement of that product over a similar product which may be just as effective.
The University of Georgia and Ft. Valley State University, the U.S. Department of Agriculture and counties of the state
cooperating. The Cooperative Extension Service offers educational programs, assistance and materials to all people
without regard to race, color, national origin, age, sex or disability.
An Equal Opportunity Employer/Affirmative Action Organization Committed
to a Diverse Work Force
Issued in furtherance of Cooperative Extension work, Acts of May 8 and June 30, 1914, The University of Georgia
College of Agricultural and Environmental Sciences and the U.S. Department of Agriculture cooperating.
Scott Angle, Dean and Director
2
TABLE OF CONTENTS
Program - Southeast Dairy Herd Management Conference
4
Program Participants ............................................................................................................ 6
Contributors and Sponsors ................................................................................................... 7
Southeast DHIA-Production and Management Trends ................................................... 8
Dr . D. W. Webb
Estrous Synchronization and Timed AlHow Much Does it Cost Per Pregnancy……………………………………………………..12
Dr. Steve Washburn
An Update on Vitamins for Dairy Cattle ……………………………………………………….17
Dr. William Weiss
Optimizing Use of Forage and Nonforage Fiber Sources When Corn is Expensive…. 30
Dr. Richard Grant
The Impact of Heat Stress on Nutrient Partitioning and Dairy Production…………….. 44
Dr. Robert Rhoads Jr.
Rethinking Nutritional Management During the Dry Period and Transition ......... …….57
Dr. James Drackley
Observation on Seasonal Pasture-Based Dairy Production .......................................... 71
Dr. Steve Washburn
Enhanced Early Nutrition for Milk-Fed Calves: What Can We Expect? …………………79
Dr. James Drackley
Dietary Factors Affecting Manure Output in Dairy Cows .............................................. 96
Dr. William Weiss
Cows Under Pressure: Recent Research on Stocking Density, Cow
Behavior, and Productivity…………………………………………………………………….106
Dr. Richard Grant
Let There be Light: Photo-Period
Management of Dairy Cattle…………………………………………………………………...118
Dr. Geoffrey Dahl
3
Southeast Dairy Herd
Management Conference
PROGRAM
Tuesday, November 6, 2007
PCDART Workshop
9:30-Noon (Georgia Farm Bureau Building)
Technical Session
11:30 Conference Registration
Afternoon
Moderator: Dr. Steve Nickerson
1:00 Welcome – Mr. Zippy DuVall, President, Georgia Farm Bureau and
Dr. Robert Stewart , University of Georgia
1:15 Trends in Southeast Dairy Production- Dr. Dan Webb
1:45 Estrous Synchronization and Timed Al-How much
Does it Cost Per Pregnancy?
- Dr. Steve Washburn
2:15 Health and Milk Production Responses to Water Soluble Vitamins
- Dr. William Weiss
2:45 Break–Sponsored by Maryland Virginia Milk Producers Co-op
3:15 Optimizing Use of Forage and Nonforage Fiber Sources When Corn
is Expensive
- Dr. Richard Grant
4:00 Defining a Metabolic Shift that Accompanies the Onset of Heat
Stress
In Dairy Cattle
- Dr. Robert Rhoads, Jr.
4:30 Rethinking Nutritional Management During the Dry Period and
Transition
- Dr. James Drackley
5:15 Questions
5:30 Reception-Sponsored by Elanco Animal Health
4
Southeast Dairy Herd
Management Conference
PROGRAM
Wednesday, November 7, 2007
Producer Session
Morning
Moderator: Dr. John Bernard
8:00 Conference Registration
9:00 Welcome – Dr. Steve Nickerson
9:15 Observations on Seasonal Pasture-Based Dairy Production
- Dr. Steve Washburn
9:45 Enhanced Early Nutrition for Milk-Fed Calves : What Can we
Expect?
-Dr. James Drackley
10:30 Break
-Sponsored by ADM Alliance Nutrition
11:00 Using Diet Formulations to Reduce Manure and Manure Nutrient
Excretion By Dairy Cows
- Dr. William Weiss
11:30 Effect of Heat Stress on Rumen Health and Post Absorptive
Metabolism In Dairy Cattle
- Dr. Robert Rhoads, Jr.
12:00 Lunch
-Sponsored by Dairy Farmers of America
Afternoon
Moderator: Dr. Joe West
1:00 Cows Under Pressure: Recent Research on Stockings Density,
Cow Behavior And Productivity
- Dr. Richard Grant
1:45 Let There be Light: Photo-Period Management of Dairy Cattle
- Dr. Geoffrey Dahl
2:15 Questions and Discussion
2:30
ADJOURN
5
Program Participants
Dr. Geoffrey E. Dahl
Head, Department of Animal Sciences
University of Florida
Dr. James Drackley
University of IIllinois
Mr. Zippy Duvall
President, Georgia Farm Bureau
Dr. Richard J. Grant
President, W. H. Miner Agricultural Research Institute
Chazy, NY.
Dr. Steve Nickerson
University of Georgia
Dr. Robert Rhoads, Jr.
University of Arizona
Dr. Robert Stewart
Head, Department of Animal and Dairy Science
University of Georgia
Dr. Steve Washburn
North Carolina State University
Dr. Dan W. Webb
University of Florida
Dr. William P. Weiss
The Ohio State University
6
Contributors and Sponsors
ADM Alliance Nutrition, Inc.
Crystal Farms
Dairy Farmers of America
Elanco Animal Health
GA Dept. of Agriculture, Animal Health
Genex Cooperative, Inc.
Intervet, Inc.
Maryland-Virginia Milk Producers Co-op
Prince Agri Products, Inc.
Southeast Milk, Inc.
Southern States Cooperative
SoyPLUS– West Central
W.B. Fleming Company
Walnut Grove Auction & Realty, Inc.
Zinpro Performance Minerals
The above organizations provided support for the conference through financial
contribution or by sponsoring a specific event. Express your appreciation to the
representatives of these organizations.
7
Southeast DHIA Herds – Production and Management Trends
Daniel W. Webb
Department of Animal Sciences, University of Florida
Southeast DHIA, Inc.
webb@animal.ufl.edu
Data from DHIA herds in Alabama, Florida, Georgia, Mississippi, South Carolina
and Tennessee were used to examine dairy production in the Southeastern
United States. Herds with data in the DRMS database as of mid-October, 2007
included: 382 Holstein herds, 58 Jersey herds and 57 herds of other breeds. In
addition, the all DRMS average from 15,574 herds located in 42 states was
used for reference.
Milk production for all 498 Southeast herds averaged 18,493 pounds (rolling
herd average) which was 325 pounds per cow above last year. The 2X-305-day
mature equivalent average was 20,690 pounds. Average 150-day milk was 62
pounds. Average peak milk was 70 pounds for first lactations and 92 pounds for
older cows.
Herd size of Southeast herds averaged 280 cows per herd, up 10 from last year
with 37% milking in lactation 1. All DRMS herds averaged 139 cows, also with
37% first lactations. Herd turn-over rate was 35 and 34%, respectively. Death
loss averaged 8.5% for Southeast herds and 9.5% for DRMS herds. Southeast
herds averaged 271 calvings and had 77 calves per 100 cows on hand. Sixtythree percent of services were to proven AI sires. Southeast herds averaged
79% heifers with known sire identity, where the average DRMS herd was 86%.
Average sire identity for adult cows was 56% for Southeast herds and 71% for
DRMS herds. Average reported milk price was $23.10, up 59% from last year’s
$14.50.
Current month pregnancy rate (September), averaged 13% for Southeast herds
and 14.8% for DRMS herds. Days to 1st service was 105 and first-service conception rate, 48%. Fifteen percent of cows were dry less than 40 days and 31%
longer than 70 days.
Average somatic cell count was 447,000 compared to last year’s 478,000.
Forty-eight percent of cows had somatic cell score below 4.0.
In comparing performance among breeds, Jersey and other breeds had lower
death loss, reduced herd exits for reproduction and notably higher pregnancy
rates.
Differences among Southeastern states were few, but Florida herds were considerably larger and Tennessee herds smaller than the average.
8
Table 1. Breed comparisons for Southeast States as of October, 2007
No. Herds
No. Cows / Herd
No. 1st Lact
% 1st Lactation
Avg Days in Milk
% Left Herd
%died
%left Repro
Milk Price
Rolling HA Milk
Rolling HA Fat
Rolling HA Prot
Summit Milk 1st Lac
Summit Milk 3rd+
Peak Milk 1st Lac
Peak Milk 3rd+
Proj 305ME Milk
Std 150-day Milk
SCC Actual
SCC Score
SCC Score 1st Lact
SCC Score 2nd Lact
SCC Score 3rd Lact
% SCC Score <4
PregRate Current mo
Actual Calving Int
Days to 1st Serv
1st Serv Concep Rate
# Calvings
# calves per 100 cows
%Dry < 40 days
%Dry > 70 days
%Bred to Proven bulls
%Bred to non-AI
%Heifers with Sire ID
%Cows with Sire ID
DRMS
Southeast
Holstein
13552
144
55
38%
195
34
9.7
6
21.40
20,934
779
640
69
91
75
100
22,976
71
333
3.1
2.7
2.9
3.6
60
14.3
14.2
98
44
145
83
16
24
64
22
86
71
Holstein
382
311
114
37%
215
34
9
6
22.80
19,236
699
589
66
86
73
96
21,601
65
455
3.6
3.2
3.5
4.1
48
11.9
14.7
106
49
300
74
15
32
64
36
78
52
* Southeast - includes 6 southeastern
states
** DRMS - includes all herds processed by DRMS
.
9
Southeast
Jersey
58
153
53
35%
189
37
6.5
3.3
24.20
14,521
651
509
48
64
54
70
16,101
47
425
3.6
3.2
3.3
4.1
50
18.3
14.3
96
43
149
99
10
28
60
20
89
90
Southeast
Other
Breeds
57
201
76
38%
200
35
6.6
5.8
23.70
17,234
649
545
58
77
64
86
19,233
58
412
3.5
3.1
3.5
3.8
51
14.5
14.3
107
47
196
77
16
34
58
37
79
55
Table 2. Southeast Comparison by State 2007.
Alabama
Holstein Herds
No. Herds
No. Cows / Herd
No. 1st Lact
% 1st Lactation
Avg Days in Milk
% Left Herd
%died
%left Repro
Milk Price
Florida
Georgia
16
170
62
36%
227
32
7.2
4.9
23.80
57
880
322
37%
206
36
11
6.3
24.10
134
366
97
27%
217
34
8.7
6.7
23.70
Rolling HA Milk
Rolling HA Fat
Rolling HA Prot
Summit Milk 1st Lac
Summit Milk 3rd+
Peak Milk 1st Lac
Peak Milk 3rd+
17,392
582
528
60
77
66
85
18,850
668
561
66
86
75
97
19,110
690
588
65
86
72
96
Proj 305ME Milk
Std 150-day Milk
SCC Actual
SCC Score
SCC Score 1st Lact
SCC Score 2nd Lact
SCC Score 3rd Lact
% SCC Score <4
PregRate Current
Actual Calving Int
Days to 1st Serv
1st Serv Concep Rate
# Calvings
# calves per 100 cows
%Dry < 40 days
%Dry > 70 days
%Bred to Proven bulls
%Bred to non-AI
%Heifers with Sire ID
%Cows with Sire ID
19,382
60
518
4.1
3.6
4
4.6
40
13
15.4
132
47
165
81
17
31
65
29
68
47
21,121
63
448
3.8
3.4
3.8
4.2
46
7.3
14.3
108
53
824
58
16
34
65
35
67
28
21,393
65
490
307
3.2
3.6
4.3
48
11
14.8
108
51
260
69
15
31
66
38
76
47
Data from DRMS - October, 2007.
10
Miss
SC
Tenn
24
241
80
33%
218
33
10.5
7.2
22.50
19,86
3
702
610
67
87
75
97
21,63
8
65
491
3.9
3.4
3.7
4.3
45
12
14.6
94
40
227
78
14
23
72
24
84
66
32
241
80
40%
218
36
7.2
6.6
22.80
20,83
7
770
645
71
95
78
105
23,65
0
69
388
3.5
3.2
3.4
4.0
52
12.9
14.4
100
48
227
91
11
26
58
30
85
65
120
146
53
36%
210
34
9.1
4.3
21.30
19,27
5
712
585
66
86
73
96
21,79
5
65
434
3.4
3.1
3.2
3.8
53
14
14.7
104
47
145
82
16
34
61
38
82
62
Table 3. Comparison of Herds in Southeast to All DRMS Herds 2007.1
All Breeds
2006
Southeast
*
533
270
97
36%
203
35
7
6
14.50
18,16
8
675
562
62
82
69
91
20,61
3
63
478
3.7
3.3
3.5
4.2
47
11
15
105
48
261
97
14
30
63
35
78
54
No. Herds
No. Cows / Herd
No. 1st Lact
% 1st Lactation
Avg Days in Milk
% Left Herd
%died
%left Repro
Milk Price
Rolling HA Milk
Rolling HA Fat
Rolling HA Prot
Summit Milk 1st Lac
Summit Milk 3rd+
Peak Milk 1st Lac
Peak Milk 3rd+
Proj 305ME Milk
Std 150-day Milk
SCC Actual
SCC Score
SCC Score 1st Lact
SCC Score 2nd Lact
SCC Score 3rd Lact
% SCC Score <4
PregRate Current
Actual Calving Int
Days to 1st Serv
1st Serv Concep Rate
# Calvings
# calves per 100 cows
%Dry < 40 days
%Dry > 70 days
%Bred to Proven bulls
%Bred to non-AI
%Heifers with Sire ID
%Cows with Sire ID
* Southeast - includes 6 southeastern
states
** DRMS - includes all herds processed
by DRMS
11
2006
2007
2007
DRMS
Southeast
DRMS
**
13,693
135
49
36%
191
33
5
5
12.74
*
498
280
103
37%
209
35
8.5
6
23.10
**
15574
139
52
37%
193
34
9.5
9.5
21.50
20,311
763
624
67
88
74
97
18,493
687
573
63
83
70
92
20,309
764
626
67
89
73
97
22,264
68
350
3.2
2.7
3.0
3.6
58
13
14
97
43
135
100
16
24
62
24
85
69
20,690
62
447
3.6
3.2
3.2
4.1
48
13
14.6
105
48
271
77
15
31
63
36
79
56
22,280
69
335
3.1
2.7
2.9
3.6
58
14.8
14.2
98
44
140
83
15
25
63
23
86
71
Estrous Synchronization and Timed AI - How Much Does it Cost Per Pregnancy?
Seven P. Washburn
Department of Animal Science
North Carolina State University
Phone: 919-515-7726
Steve_Washburn@ncsu.edu
Objectives: The objectives of this paper and presentation are to review trends
in reproduction in
dairy cattle, to examine ranges of efficacy and costs of synchronization programs, and to touch on other approaches to improve reproduction of dairy cattle
in the long run.
Would you consider a 21-day pregnancy rate of 20% to be good for your
herd?
On many farms where cows are housed continually on concrete surfaces, detection of estrus is no longer done routinely. In such herds, use of tail paint or
chalk, pedometers to measure activity, or intensive use of synchrony products
followed by timed AI are more often the tools used to produce pregnancies. The
first National Reproduction Council meeting in 2006 and in the April 10 issue of
Hoard’s Dairyman (Jordan, 2007 and Ellen Jordan, personal communication),
information was reported from 8 dairy herds that had achieved 21-day pregnancy rates of 17 to 25% which are all well above a national average of about
14%. Three of those 8 herds were located in the South (NC, VA, and TX) and all
3 Southern herds had freestall facilities with 900, 2,300, or 2,500 Holsteins, respectively. The Southern herds all had 21-day pregnancy rates at about 19 to
20 percent which means that an average of 19 to 20% of eligible cows in the
breeding herd successfully become pregnant during each 21-day period. The
Southern herds reported first service conception rates of 31 to 35% and annual
average conception rates of only 25 to 28% with just about half (47 to 53%) of
the cows conceiving by 150 days in milk. The VA herd uses pedometers for detection of estrus and the other two herds use a tail chalking system and an aggressive program for synchronization and timed breeding. The two herds from
NC and VA had about 7.5% abortions after 42 days whereas the Texas herd
reported 15.6% abortions. Those 3 herds were presented among 8 herds as
good examples for getting cows pregnant!
Trends of declining reproductive performance of dairy herds in the Southeast
and elsewhere are of concern, particularly the severe decline observed beginning in the mid 1980’s (Washburn et al, 2002a). Herds in all 10 states studied
increased days open between 39 days (VA) and 57 days (GA-FL) over the 24year period from 1976 to 1999. Days open increased in both Jersey and Holstein herds and services per conception more than doubled in that time and are
at or near 3 services, indicative of conception rates below 35%. Although in
herds with both Jersey and Holstein cows, Jerseys usually have higher fertility
(Washburn et al., 2002b), decline in fertility was evident in Jersey herds across
time. Specific causes of lower reproductive success are not clear, but multiple
factors have likely contributed. Similarly, there may be diverse strategies for differing herd management situations in approaching herd reproductive management. I believe that it is a fair assumption that many dairy producers in the
Southeast are not satisfied with the reproductive success of their dairy cattle,
particularly the fertility of lactating cows.
12
How many injections per pregnancy and at what cost?
One reproductive strategy that is becoming widely used is to manipulate cattle
estrous cycles to induce ovulation by using commercially available products
containing prostaglandin F2α or its analogs (PGF), gonadotropin releasing hormone (GnRH), progesterone (P4). These products have been used in increasingly complex combinations to ensure a high probability that cows will be at the
right stage of the estrous cycle to have a high probability of ovulation and hopefully conception after a series of treatments. This has led to a “new” vocabulary
of terminology including Ovsynch, Presynch, Cosynch, Select Synch, Modified
Ovsynch, and CIDR-Synch, among other synchronization programs.
In the May 25 issue of Hoard’s Dairyman, Drs. Jenks Britt, Jeff Stevenson, and I
reported calculated pregnancy results and costs of a 3-cycle synchronization
program in a 100-cow herd using timed artificial insemination (TAI) followed by
use of a clean up bull after three TAI services (Britt et al., 2007). The three synchronization cycles modeled were 1) Pre-Synch plus Ovsynch for the first
breeding cycle; 2) GnRH injections given to all inseminated cows 7 days before
pregnancy check and completing Ovsynch for all nonpregnant cows for cycle
two; and 3) CIDR-Synch (CIDR inserted at the time of GnRH injection 7 days
before pregnancy diagnosis) on all third cycle cows.
We examined the effect of differing conception rates on synchrony costs by using a base rate at 30% success for TAI in comparison to success rates of 20,
25, 35 and 40%. Unit prices of the products used were $2.60 for PGF, $3.30 for
GnRH, and $9.50 for a CIDR.
At the 30% conception rate, 957 total injections (and CIDR applications) are
needed per 100 cows. A conception rate of only 20% would increase total synchrony treatments to 1,032 per 100 cows, whereas improving conception rate to
40% would reduce total synchrony treatments to 888. At a 20% conception rate,
it would take 21.1 doses of synchronization products per AI pregnancy, whereas
only 11.4 doses are needed per AI pregnancy if TAI conception rates of 40%
are achieved.
The program at 30% conception rate would result in 66 AI-sired pregnancies per
100 cows when checked at 42 to 45 days post breeding. Fetal loss would result
in 59 pregnancies reaching term with 55 live births of which 27 (48%) would be
female. Twenty six of those females would calve and enter the milking herd. If
all injection costs were applied to the females entering the herd then the approximate cost would be $122 per cow. At the 20% conception rate, only 49
pregnancies and 19 AI-sired females per 100 cows would be expected to enter
the herd at an injection cost of $184 each, whereas 78 pregnancies and 31 AIsired females per 100 cows would enter the herd at a synchronization cost of
only $93 each if the TAI conception rate reached 40%.
Exact compliance to the synchronization injection/application schedule is critical
for success of any program using estrous synchronization. If herd workers do
observe cows in standing estrus at times not consistent with protocols for TAI,
then such cows should be inseminated accordingly rather than waiting to synchronize and use TAI. Cows conceiving to AI at observed estrus rather than being synchronized for TAI, reduce costs in the range of $37 to $71 in injections/
application cost per pregnant cow compared to being synchronized.
13
Variations in the Ovsynch program published last year (Bello et al; 2006) feature
3 injections of GnRH and 2 injections of PGF over a 15- to 17-day period. The
additional injections ensure that most cows are early in the cycle when Ovsynch
begins, leading to increased ovulatory response and likely improved conception.
Those workers reported that highest synchronization of ovulation and highest
conception rate resulted from using an initial injection of PGF (day 1) followed
two days later with GnRH (day 3), then starting Ovsynch using GnRH again 6
days later (day 9), PGF 7 days later (day 16), GnRH 2 days later (day 18), followed by timed insemination on day 19. Plugging in cost figures for the 5injection regimen at 50% conception (10 injections per pregnancy) would result
in about $30.20 per pregnancy for synchrony products compared to 26.5% conception and $34.72 per pregnancy using the simpler 3-injection Ovsynch (11.3
injections per pregnancy) but with only just about half the number of pregnant
cows. The results look promising but with only about 30 cows per treatment and
pregnancies determined at 35 days, more data are needed to see if those responses remain consistent and if a high percentage of pregnancies are carried
to term. Certainly, if pregnancy losses after 35 days were as high as 15%, such
a regimen for controlling ovulation would be less attractive.
Back to the question: Would you consider a 21-day pregnancy rate of 20%
to be good for your herd? If you are one of those herds near the national average of 14% then a 21-day pregnancy of 20% would look really good and 22 to
25% would be even better as achieved by a small percentage of large, high producing dairy herds with use of synchronization and timed AI.
In contrast, for herds that breed cows seasonally so that most of the herd would
calve within 60 to 90 days, then a 21-day pregnancy rate of 25% would be very
poor. For such herds, optimal submission rates for insemination in the first 21
days of the breeding season would be above 90% with conception rates at
about 50 to 60% resulting in 21-day pregnancy rates in the range of 45 to 55%.
There are herds in our part of the United States that are reaching such levels of
reproductive efficiency without extensive use of estrous synchronization. Reproductive success certainly is a relative term!
What are some longer term options for reproductive management in dairy
herds?
Markedly reduced synchronization costs per cow that are demonstrated by
achieving greater conception rates should be incentive for producers to try and
improve conception and pregnancy rates in their herds. Such strategies would
include monitoring of nutritional programs to ensure most cows are cyclic within
a few weeks after calving. It is particularly important to have excellent cow care
and nutritional management during the transition from dry period through early
lactation. Although there is quality control on processing semen for AI, there can
still be significant differences in fertility of individual bulls as measured by estimated relative conception rates (ERCR). Also, since 2003, the availability of
daughter pregnancy rate (DPR) estimates for bulls provides a genetic basis for
improving dairy cow fertility in the long run. Discussed briefly below are a few
different approaches to consider for managing reproduction in dairy herds in
addition to the various programs of synchronization and timed breeding.
14
Management of cows through the transition period is critical to most aspects
of dairy farm success. There have been numerous studies that indicate that
cows starting a new lactation with a metabolic problem, mastitis, lameness, dystocia, retained placenta, or uterine infection are less likely to have normal estrous cycles after calving and therefore unlikely to rebreed successfully in a
timely manner. In fact, the more complicated methods of synchronization are
aimed at cows that have not started to cycle in the early postpartum period. Important management practices include use of calving ease sires for mating heifers, well-balanced nutrition and gradual ration changes, as well as very close
observation during transition to head off small problems before they become
management nightmares.
Longer lactations may be more desirable in some environments. Because our
modern dairy cattle have been selected for milk production over many generations, there likely are high proportions of cows that can remain very productive
for lactations extending well beyond 15 months. In fact, New Zealand researchers are experimenting with the economics of breeding some cows every other
year and milking them for about 22 months in each lactation. This would allow
cows much longer time to recover from any adverse conditions in early lactation. Planned longer lactations for cows in Southeastern U.S. herds may provide
some flexibility for avoiding breeding during periods of extreme environmental
heat stress. Such strategies may be competitive with the more elaborate systems of cooling cows although cooling cows generally provides benefits in production and health as well as improving reproduction.
Heritability of reproductive traits is not high but there is now an opportunity to
gain reproductive efficiency by placing stronger emphasis on semen fertility
(ERCR) as well as the expected fertility of daughters of AI bulls or daughter
pregnancy rate (DPR). The current (2006) Net Merit$ index and Fluid Merit$
index from USDA (http://aipl.arsusda.gov/eval.htm) include 9% weighting and
8% weighting, respectively for DPR. Although the estimated heritability of DPR
is only 4%, it is expected that routine consideration of fertility in sire evaluations
will help stabilize fertility in dairy cattle while continuing to make progress with
milk production other traits of economic importance. In fact, doubling the Net
Merit$ index weighting to 18% for DPR results in only slightly lower predicted
transmitting ability for milk yield (1254 pounds vs. 1198 pounds or only 4.5%
lower with twice the emphasis on reproduction) and Net Merit$ ($484 vs. $460
or just 5.0% lower with twice the emphasis on reproduction) among the top 10%
of active AI Holstein bulls. This suggests that even more emphasis on genetic
selection for fertility can be accomplished without having unreasonably adverse
effects on production. Another way of approaching this issue is to select the top
bulls using the selection index of choice and then avoid using bulls that are
negative for DPR. In herds breeding groups of cows seasonally, these genetic
aspects may be even more critical than in herds calving year around.
15
Crossbreeding is another strategy to consider. The large Holstein cow is likely
the most susceptible to environmental heat stress. Holsteins make up more
than 90% of the national dairy herd for a very good reason – they are efficient
and very high-producing milking beasts. However, data on crossbreeding look
promising as other factors of economic performance are considered. Jerseys,
Milking Shorthorns, and Ayrshires all have a higher average DPR than Holsteins, whereas Brown Swiss and Guernsey are lower than Holsteins by 0.6 and
1.1 percentage units, respectively (http://aipl.arsusda.gov/eval.htm). With the
estimated heterosis for DPR at 1.5 percentage units, average DPR across many
crossbred combinations likely will exceed Holsteins for fertility. Similarly, other
European dairy breeds used recently in this country also have promising reproduction when crossed with Holsteins. There is also some expected hybrid vigor
for production as well as likely advantages for crossbreeding in health and other
fitness traits such as calving ease. Of course, potential advantages must be
evaluated economically within the context that overall milk production of crossbred dairy cows will generally be lower than milk production of Holsteins.
Summary: We have developed increasingly complex regimens of hormonal
treatments to more effectively synchronize the timing of ovulation in dairy cattle
such that breeding can be accomplished without the use of estrous detection.
However, after many years of selection for milk production without consideration
of reproduction, fertility has declined in dairy cattle such that the number of
treatments per pregnancy and the associated costs for getting cows pregnant
continues to rise. Costs per pregnancy of synchronization programs are closely
tied to the underlying expected fertility of the herd. It is not reasonable to continue to add complexity to methods of synchronization of cattle without also
dealing with underlying causes of lower fertility. Strategies for dealing with herd
reproduction include improving nutrition and management during the transitional
period, intentional use of longer lactations, cow cooling practices and/or avoiding breeding in times of extreme environmental heat stress, using semen of high
fertility (estimated relative conception rate – ERCR), more emphasis on daughter pregnancy rate (DPR) in genetic selection, and planned use of crossbreeding to improve fertility and other fitness traits. No one approach suits all dairy
farm situations but one definition of insanity is to continue to do the same thing
and to expect different results!
Acknowledgements: Portions of this paper are adapted from an article that
appeared in the May 25th 2007 issue of Hoard’s Dairyman. The input of Dr.
Jenks Britt of Western Kentucky University and Dr. Jeff Stevenson of Kansas
State University in the original article is recognized and appreciated.
Bello, N. M. J. P. Steibel, and J. R. Pursley. 2006. Optimizing Ovulation to First
GnRH Improved Outcomes to Each Hormonal Injection of Ovsynch in Lactating
Dairy Cows J Dairy Sci 89: 3413-3424.
Britt, Jenks, Steve Washburn, and Jeff Stevenson. 2007. Timed A.I. – What
does that pregnancy really cost? Hoard’s Dairyman. May 25, 2007. p 396.
Jordan, Ellen. 2007. Top repro herds get cows pregnant. Hoard’s Dairyman.
April 10, 2007. p 253.
Washburn, S.P., W.J. Silvia, C.H. Brown, B.T. McDaniel, and A.J. McAllister.
2002a. Trends in reproductive performance in Southeastern Holstein and Jersey DHI herds. J. Dairy Sci. 85: 244-251.
16
Washburn, S.P., S.L. White, J.T. Green, Jr., and G.A. Benson. 2002b. Reproduction, mastitis, and body condition of seasonally calved Holstein and Jersey
cows in confinement or pasture systems. J. Dairy Sci. 85: 105-111.
17
An Update on Vitamins for Dairy Cattle
William P. Weiss
Department of Animal Sciences
Ohio Agricultural Research and Development Center
The Ohio State University, Wooster
Summary Points
1. Supplementing fat- and water-soluble vitamins properly can increase milk
production and/or improve animal health resulting in increased profitability but
adding excess or unneeded vitamins increases feed costs and can reduce profitability.
2. All diets fed to dairy cows (dry and lactating) should be supplemented with
vitamins A (approximately 90,000 IU/day), D (15,000 to 25,000 IU/day) and E
(500 to 5000 IU/day).
3. Supplementing biotin at approximately 20 mg/day can improve hoof health
and reduce lameness. Milk production often, but not always, increases.
4. Supplementing niacin at approximately 6 g/day is unlikely to affect health or
milk production. Some production responses might be observed at 12 g/day.
5. Rumen-protected choline fed the first few months of lactation usually increases milk production and is often profitable but profitable responses are less
likely later in lactation.
6. Inadequate data are available to recommend supplementing other vitamins at
this time.
Introduction
Vitamins are organic compounds needed in minute amounts that are
essential for life. A vitamin must be in the diet or be synthesized by microorganisms in the digestive system and then absorbed by the host animal. Currently
there are 14 recognized vitamins of which four are fat-soluble and ten are watersoluble, but not all animals require all 14 vitamins (Table 1). When an animal
absorbs an inadequate quantity of a particular vitamin, various responses are
observed depending on the vitamin and the degree and duration of deficiency.
The most severe situation (seldom observed in U.S. dairy cows) is a clinical deficiency. Marginal deficiencies of vitamins usually have more subtle and less
defined signs but can include reduced growth and milk production, poor reproduction and increased prevalence of infectious diseases. The purpose of this
paper is to provide an update on new research on vitamins for dairy cows. Research in the past few years has concentrated on water soluble vitamins; therefore those vitamins will be discussed more. However, all cows should be fed
supplemental fat-soluble vitamins but not all cows need to be supplemented
with water soluble vitamins.
18
Fat Soluble Vitamins
Although vitamins A, D, and E are essential to cows, not much new information is available on those vitamins. No data are available refuting current
recommended (NRC) supplementation rates for vitamins A and D. Because of
variability and other unknown factors, diets should be formulated to provide
20,000 to 30,000 IU of vitamin D per day and 85,000 to 100,000 IU/day of vitamin A. Exceeding these rates of supplementation are unlikely to have any positive effect. Some newer information is available regarding vitamin E. The NRC
recommends that lactating cows consume about 500 IU/day of vitamin E and
dry cows consume about 1000 IU/day. Several experiments have reported that
feeding prefresh cows (2 to 3 weeks before calving) more than 1000 IU/day can
be beneficial with respect to mammary gland and/or uterine health. Supplementation rates varied among experiments (2000 to 5000 IU/day of supplemental
vitamin E), therefore a specific recommendation cannot be determined, but prefresh cows fed hay or silage will probably benefit by supplementing at least
2000 IU/day of vitamin E. Other experiments suggest that prefresh cows that
are grazing do not need more than 1000 IU/day and may need even less vitamin E.
Water Soluble Vitamins
We do not know whether cows have an absolute dietary requirement for
any of the water soluble vitamins. The liver and kidney of the cow can synthesize vitamin C, and ruminal and intestinal bacteria synthesize most, if not all, of
the B-vitamins. The concentrations of many B-vitamins are relatively high in
many common feeds, therefore, in the vast majority of situations cows do not
need to consume any supplemental water soluble vitamins to prevent clinical
deficiency. Based on a survey of the highest producing dairy herds in the US
conducted in 2000 (Kellogg, 2001) the only water soluble vitamins fed were niacin (43% of the surveyed herds), and choline and biotin (<4% of surveyed
herds).
The predominant function of the B-vitamins is to act as co-factors for enzymes that are involved in amino acid, energy, fatty acid, and nucleic acid metabolism (Table 1). Many of these enzymes are involved directly in the production of milk and milk components. Therefore, as milk production increases, the
need for these enzymes increase. In the past 15 years, average milk yield per
cow has increased from about 14,500 lbs per year to almost 19,500 lbs and
herds (not individual cows) that average 28,000 lbs or more per cow are not uncommon. Assuming average milk composition, an average Holstein in 2005
must synthesize approximately 0.4 lbs more milk fatty acids (assuming 50% of
milk fatty acids come from the diet), 0.6 lbs more milk protein and 0.9 lbs more
lactose each day than the average cow in 1990. During that same period, average dry matter intake has increased from about 44 lbs to about 50 lbs/day. In
other words, the yield of milk and milk components has increased about 33%,
but dry matter intake has increased only about 15%. Because most B-vitamins
are not supplemented, supply to the cow would mostly be a function of intake
whereas their need would be a function of milk production. The potential imbalance between supply and need in today’s high producing cow increase the likelihood that responses will be observed when B-vitamins are supplemented.
19
B-Vitamin Supply
As with all nutrients, a response to supplementation of B-vitamins will
only be observed if supplementation actually increases the supply of vitamin to
the tissues that require it. Vitamin supply is the amount (micrograms or milligrams) of a vitamin that is absorbed from the digestive system each day and is
a function of the amount of the vitamin consumed, ruminal synthesis and degradation of the vitamin, and absorption by the small intestine.
Dietary Concentrations
Ranges in reported concentrations of various B-vitamins in diets fed to
lactating cows are in Table 2 (very limited data). Considering the analytical and
sampling error usually observed when trace nutrients are measured, concentrations of most of B-vitamins were relatively consistent across the diverse diets
with the clear exception of niacin. Niacin concentrations in the diet were positively correlated with the concentration of soyhulls in the diets (i.e., soyhulls had
high concentrations of niacin). Additional data are needed to confirm whether
soyhulls typically contains such high concentrations of niacin. The biotin concentration of different diets within an analytical method did not vary greatly but
method of analysis had a substantial effect (Table 2). Biotin concentrations
measured using one analytical procedure averaged about 7 mg/kg and in other
studies using a different procedure it was almost 20 times lower (about 0.4 mg/
kg). At the current time, we do not know which method is correct.
Ruminal Metabolism
For most B-vitamins, flow out of the rumen exceeds intake indicating net
synthesis in the rumen (Table 3). With the exception of biotin and vitamin B-6,
ruminal synthesis appears to provide the majority of the B-vitamins that reach
the small intestine (Table 3). Diet probably affects the amount of B-vitamins
produced in the rumen but only one study is available relating diet to vitamin
synthesis in dairy cows (Schwab et al., 2006). In that study, generally diets that
were more fermentable (more starch and less fiber) stimulated synthesis of
most B-vitamins. The exception was B-12 synthesis which was reduced as
starch increased.
Based on limited research, most supplemental B-vitamins are extensively metabolized in the rumen.
A study from Wisconsin (Santschi et al.
2005a) reported that approximately 100% of supplemental riboflavin, niacin, and
folic acid, 66% of supplemental thiamin and B-12, and about 40% of supplemental B-6 and biotin disappeared in the rumen. For vitamins with high disappearance rates, they must either work in the rumen or they must be protected
from rumen degradation if they are to be effective.
Clinical and Production Responses to B-vitamins
Niacin
Niacin is involved in most energy-yielding pathways and for amino acid
and fatty acid synthesis and therefore is important for milk production. Numerous studies have been conducted evaluating the effect of niacin supplementation on milk yield. Schwab et al (2005) combined results from several previous
studies and used a new statistical method to evaluate overall responses to niacin.
20
They concluded that supplementing 6 g/d of niacin had no effect on milk production or milk composition. At 12 g/d of supplemental niacin, 3.5% fat-corrected
milk increased about 1 lb/d, fat yield was increased 26 g/d and milk protein yield
was increased 17 g/d. Based on the current cost of niacin, this response would
often not be profitable. The likelihood of a profitable response can be increased
by targeting specific animals. Positive responses appear more likely in early
lactation, high producing cows and responses are almost never observed in
mid and late lactation cows (Girard, 1998). One reason supplemental niacin
may not have an effect is that most of it is metabolized in the rumen. A rumenprotected form of niacin is available but published data evaluating the product
with dairy cows are not available.
Niacin also has been evaluated as a ketosis treatment and/or preventative but the vast majority of studies show that at rates of 6 to 12 g/d, niacin is not
effective at reducing ketosis. Recently, a study from Oregon showed very positive effects when Jersey cows were fed 48 g of nicotinic acid/day from 30 d prepartum until calving but when this study was repeated with Holstein cows, a
similar rate of niacin had no effect.
Biotin
Six clinical trials have been published on the effect of supplemental biotin on hoof horn lesions and lameness in dairy cows (reviewed by Weiss, 2005).
Although the response variable varied among experiments, all studies reported
reduced prevalence of specific lesions or clinical lameness when biotin was
supplemented. The supplementation rate was 20 mg/d in most studies but one
study with beef cows fed only 10 mg/d and reported a positive response, and all
studies involved long term (months) biotin supplementation. Biotin supplementation usually reduces hoof lesions in two to three months but six months of supplementation may be required to reduce clinical lameness. The mechanisms by
which biotin affects foot health are not well understood.
Milk yield responses to supplemental biotin are less consistent than hoof
responses, but the majority of studies reported increased production (Table 4).
Low producing cows and/or cows in late lactation are unlikely to increase milk
yield when biotin is supplemented. A recent 14-day study from our laboratory
found that biotin increased milk yield when supplemented to high-producing
dairy cows (control cows average production = 89 lbs/day and 136±56 days in
milk), but not when supplemented to low-producing dairy (average production
for control cows = 52 lbs/day and 267±53 days in milk). The lack of a production response by low producing cows in that study agree with data from Australia (Fitzgerald t al., 2000). The reason cows in the Rosendo et al. (2004) experiment did not respond is not known (milk production of control cows averaged 79
lbs/day). Across all studies, the median increase in milk yield was 2 to 3 lbs./
day. Whereas months of supplementation are required to observe improved
hoof health, the milk yield response appears very rapidly (Figure 1). The
mechanism by which biotin supplementation increases milk yield is not known,
but we have found that supplemental biotin can increase the activity of one gluconeogenic enzyme in the liver of dairy cows.
21
Other Water Soluble Vitamins
Research is extremely limited on the effects of supplementing other water soluble vitamins to dairy cows. Canadian studies of folic acid supplementation (typical rates are between about 2 and 3 g/day) have produced variable results on milk production. In one study milk production of multiparous cows was
increased by 4 to 6 lbs/d when folic acid was supplemented, but no effect was
observed with first lactation cows. In other experiments folic acid has not affected milk production. One reason for the variable responses maybe that vitamin B-12 status was limiting. If cows are limited in B-12, they are unlikely to
respond to folic acid supplementation. In a study from Wisconsin a mixture of
B-vitamins (biotin, folic acid, niacin, pantothenic acid, B-6, riboflavin, thiamin,
and B-12) was fed, and milk production was increased compared with the control but was not different from a treatment in which only biotin was supplemented. When the amount of supplemental B-vitamins was doubled, intake and
milk production was similar to control cows (i.e., lower than the 1-X supplementation treatment). Shaver and Bal (2000) examined the effects of supplemental
thiamin on milk production. In one experiment, yield of milk, milk fat, and milk
protein increased when cows were fed 150 mg of thiamin per day. In two other
experiments, cows fed thiamin at 300 mg/day had similar milk yields as control
cows. Some experiments with dairy cows have shown some health benefits
when vitamin C is injected and other experiments have shown links between
vitamin C status and severity of mastitis. At this time, vitamin C for dairy cows
is purely experimental. Overall, the available data do not support routine supplementation of ‘other’ B-vitamins or vitamin C. However, as productivity of
cows continue to increase and as new experiments are conducted, this conclusion may change.
Choline
Choline does not fit the definition of a vitamin. It is required in gram
quantities (not milligram or microgram quantities) and it is synthesized by the
cow. Very little, if any, dietary choline (with the exception of rumen-protected
supplements) is absorbed from the gut because it is degraded in the rumen.
Twelve separate comparisons on effects of feeding rumen-protected choline are
available (most were conducted with cows during the first 2 months of lactation).
In 7 of the studies, cows fed choline had a statistically significant increase in
milk production and in 11 of the studies, milk production was numerically higher
when choline was fed. The median increase in milk production when rumenprotected choline was fed was about 5 lbs./day. The cost of rumen protected
choline is high but at today’s high milk price, it should be profitable to supplement early lactation cows. In addition to effects on milk production rumen protected choline during the transition period may reduce liver fat but results have
not been consistent.
22
Conclusions and Recommendations
1. Feed dry and lactating cows, diets that provide about 25,000 IU/day of vitamin D and 90,000 IU/day of vitamin A.
2. During the prefresh period, cows fed silage or hay should be supplemented
with 2000 to 5000 IU/day of vitamin E. During the rest of the dry period, 1000
IU/day and during lactation 500 IU/day should be adequate. Grazing cows
probably need little vitamin E supplementation.
3. Supplemental biotin provided at about 20 mg/day has consistently improved
hoof health and increased milk production in several, but not all, studies. For
improvements in hoof health biotin must be fed for several months (including
the dry period) but increased production will happen within a very short period.
Feeding 20 mg/day of biotin to lactating and dry cows is recommended because
of its effects on foot health.
4. Rumen-protected choline fed at 50 g/day (actual product, not choline) has
resulted in increased milk production in most studies and reduced liver fat in
some studies. The cost of supplementation is substantial but the median response to supplementation was about 5 lbs of milk/day. A response in milk production is most likely in early lactation (up to about 60 days in milk) and to maximize the likelihood of a profitable return on investment, supplementation should
be limited to early lactation cows.
5. A milk production response to niacin supplementation at 6 g/day is unlikely,
but supplementation at 12 g/d can increase milk production by about 1 lb (likely
not a profitable return on investment). A positive return on investment is more
likely when supplementation is limited to early lactation cows. The use of supplemental niacin in herds that feed a single diet to all cows is unlikely to have a
positive return on investment.
6. At this time, insufficient data are available to recommend supplementation of
other B-vitamins and vitamin C to dairy cows.
References
Bergsten, C., P. R. Greenough, J. M. Gay, W. M. Seymour, and C. C. Gay.
2003. Effects of biotin supplementation on performance and claw lesions
on a commercial dairy farm. J. Dairy Sci. 86:3953-3962.
Ferreira, G., W. P. Weiss, and L. B. Willett. 2007. Changes in measures of biotin status do not reflect milk yield responses when dairy cows are fed
supplemental biotin. J. Dairy Sci. 90:1452-1459
Fitzgerald, T., B. W. Norton, R. Elliott, H. Podlich, and O. L. Svendsen. 2000.
The influence of long-term supplementation with biotin on the prevention
of lameness in pasture fed dairy cows. J. Dairy Sci. 83:338-344.
Girard, C. L. 1998. B-complex vitamins for dairy cows: a new approach. Can. J.
Anim. Sci. 78 (Suppl. 1):71-90.
23
Kellogg, D. W., J. A. Pennington, Z. B. Johnson, and R. Panivivat. 2001. Sur
vey of management practices used for the highest producing DHI herds
in the United States. J. Dairy Sci. 84 (E suppl.):E120-E127.
Majee, D. N., E. C. Schwab, S. J. Bertics, W. M. Seymour, and R. D. Shaver.
2003. Lactation performance by dairy cows fed supplemental biotin and a
B-vitamin blend. J. Dairy Sci. 86:2106-2112.
Margerison, J. K., B. Winkler, and G. Penny. 2002. The effect of supplemental
biotin on milk yield, reproduction, and lameness in dairy cattle. 22nd
World Buiatrics Congress, Hanover, Germany:219.
Midla, L. T., K. H. Hoblet, W. P. Weiss, and M. L. Moeschberger. 1998. Supplemental dietary biotin for Prevention of lesions associated with aseptic
subclinical laminitis ( pododermatitis aseptica diffusa)
In primiparous cows. Amer J Vet Res. 59(6): 733-738.
Rosendo, O., C. R. Staples, L. R. McDowell, R. McMahon, L. Badinga, F. G.
Martin, J. F. Shearer, W. M. Seymour, and N. S. Wilkinson. 2004. Effects
of biotin supplementation on peripartum performance and metabolites of
Holstein cows. J. Dairy Sci. 87:2535-2545.
Santschi, D. E., R. Berthiaume, J. J. Matte, A. F. Mustafa, and C. L. Girard.
2005a. Fate of supplementary B-vitamins in the gastrointestinal tract of
dairy cows. J. Dairy Sci. 88:2043-2054.
Santschi, D. E., J. Chiquette, R. Berthiaume, R. Martineau, J. J. Matte, A. F.
Mustafa, and C. L. Girard. 2005b. Effects of the forage to concentrate ratio on B-vitamin concentrations in different ruminal fractions of dairy
cows. Can J Anim Sci. 85:389-399.
Schwab, E. C., D. Z. Caraveillo, and R. D. Shaver. 2005. Review: A metaanalysis of lactation responses to supplemental dietary niacin in dairy
cows. Prof. Anim. Sci. 21:239-247.
Schwab, E. C., C. G. Schwab, R. D. Shaver, C. L. Girard, and D. E. Putnam.
2006. Dietary forage and nonfiber carbohydrate contents influence Bvitamin intake, duodenal flow, and apparent ruminal synthesis in lactating
dairy cows. J. Dairy Sci. 89:174-187.
Shaver, R. D. and M. A. Bal. 2000. Effect of dietary thiamin supplementation on
milk production by dairy cows. J. Dairy Sci. 83:2335-2340.
Weiss, W. P. 2005. Update on vitamin nutrition of dairy cows. New England
Dairy Feed Conf, W. Lebanon, NY:30-40. See: http://dairy.osu.edu/
resource/feed/Vitamin%20update.pdf
Zimmerly, C. A. and W. P. Weiss. 2001. Effects of supplemental biotin on performance of Holstein cows in early lactation. J. Dairy Sci. 84:498-506.
24
Table 1. Compounds currently recognized as vitamins
General function
Fat-soluble vitamins
Vitamin A
Gene regulation, immunity, vision
Vitamin D
Ca and P metabolism, gene regulation
Vitamin E
Antioxidant
Vitamin K
Blood clotting
Water-soluble vitamins
Biotin
Carbohydrate, fat, and protein metabolism
Choline
Fat metabolism and transport
Folic acid
Nucleic and amino acid metabolism
Niacin
Energy metabolism
Pantothenic acid
Carbohydrate and fat metabolism
Pyridoxine (vitamin B6) Amino acid metabolism
Riboflavin
Energy metabolism
Thiamin
Carbohydrate and protein metabolism
Vitamin B12
Nucleic and amino acid metabolism
Vitamin C
Antioxidant, amino acid metabolism
25
Table 2. Concentrations of B-vitamins in cattle diets and typical vitamin intakes by dairy cattle. Data are from 7 different diets fed in 3 experiments
(Santschi et al., 2005a; Santschi et al., 2005b; Schwab et al., 2006). All analyses (except where noted) were conducted in a single laboratory.
Vitamin
Average, mg/kg
DM
Range, mg/kg
DM
Mean Intake, mg/day1
Thiamin
2.0
1.5 to 2.6
45
Riboflavin
5.4
4.3 to 6.7
123
Total niacin
46.0
22.6 to 94.8
1045
Vitamin B-6
5.2
3.2 to 8.5
118
Total folates
0.5
0.4 to 0.7
11
Biotin
6.9
6.3 to 7.8
157
Biotin2
0.37
0.33 to 0.41
8
1
Based on an average dry matter intake of 50 lbs/day
2
Biotin data in this row are from three different diets (Zinn, et al., 1987;
Frigg et al., 1993; Midla, et al., 1998) and the analytical methods used
were different from that used in the other experiments.
26
Table 3. Net ruminal synthesis of B-vitamins by dairy cattle (data derived
from (Santschi et al., 2005a; Schwab et al., 2006). Synthesis values are
Net ruminal synthesis
Vitamin
Ruminal
mg/kg of DM intake mg/day1 Total flow1,2,
mg/day
synthesis, %
of total flow
Thiamin
2.3
51
96
53.1
Riboflavin
12.1
274
397
69.0
Total niacin
62.8
1425
2470
57.7
Vitamin B-6
0.9
21
139
15.1
Total folates
0.9
19
30
63.3
0
0
157 (8)3
0
3.9
88
88
100
Biotin
Vitamin B12
1
Based on an assumed DM intake of 50lbs/day
2
Flow measured at the duodenum and equals the sum of vitamin intake
(Table 2) and net synthesis.
3
The number in parenthesis is intake based on a different analytical
technique (see Table 2).
27
Table 4. Summary of reports on effects of biotin supplementation on milk
yield.
Treatment
Results
Re
f1
0 or 20 mg/day until 300 DIM
Treatment increased 305 d ME by 1
680 lbs (P < 0.05). Control ME =
25,900 lbs
0 or 20 mg/d for 13 months
No effect on milk yield. Yield was
42 lbs./day for control
2
0 or 20 mg/d for first 120 DIM
Treatment increased (P < 0.05)
yield from 82 to 86 lbs./day
3
0 or 20 mg/d for 14 months
Treatment increased 305 day milk 4
by 1060 lbs (P < 0.05). Control
milk = 22,200 lbs
0, 10, or 20 mg/d until 100 DIM
Linear (P < 0.05) effect. Yields
were 81, 83, and 87 lbs./day
5
0 or 20 mg/d for 28 d periods
Treatment increased (P < 0.05)
yield from 82 to 84 lbs/day
6
20 or 40 mg/d for 28 d periods
No effect, average yield = 90 lbs./ 6
day
0 or 30 mg/d until 70 DIM
No effect on 4% FCM yield, average = 76 lbs./day
7
0 or 20 mg/d for 14 d starting at Treatment increased (P < 0.05)
136 DIM
yield from 89 to 100 lbs./day
8
0 or 20 mg/d for 14 d starting at No effect, average yield = 52 lbs/
267 DIM
day
8
1
References were: 1) Midla et al., 1998; 2) Fitzgerald et al., 2000; 3)
Margerison et al., 2004; 4) Bergsten et al., 2003; 5) Zimmerly and
Weiss, 2001; 6) Majee et al., 2003; 7) Rosendo et al., 2004; 8) Ferreira
et al., 2007.
28
Figure 1. Milk yield response when cows in mid (136 days in milk) or late
(267 days in milk) were supplemented with 20 mg/day of biotin (Ferreira et al.,
2007). Dashed lines represent control cows and solid lines represent supplemented cows. Arrows designate when supplementation started and ended.
120
Mid lactation cows
Milk yield, lbs./day
100
80
60
40
Late lactation cows
20
0
-7
0
7
14
Experimental day
29
21
28
Optimizing Use of Forage and Nonforage Fiber Sources When Corn is Expensive
Rick Grant
William H. Miner Agricultural Research Institute
Chazy, NY 12921
518-846-7121 x116
grant@whminer.com
Introduction
For many years, relatively inexpensive corn grain has resulted in corn being
used in ration formulation to provide fermentable carbohydrate that provides
energy to the rumen microflora and the cow. There have been several recent
reviews that discussed factors that influence the optimal amount of starch to
include in dairy cattle rations to optimize microbial fermentation and consequently cow performance (ex. Grant, 2005). Recently, the price of corn has
risen dramatically as well as some other grains and byproduct feeds. Consequently, we need to reassess how corn grain is used in ration formulation and
what alternative feeding strategies are possible under conditions of high-priced
corn.
Although there are several combinations of approaches that may be used depending on geographical location and prevailing local conditions, the three basic
feeding strategies are: 1) feeding more forage and less grain, 2) feeding higher
quality forage which is necessary if forage comprises more of the diet, and 3)
making use of byproduct feeds as both grain and forage replacements. Often,
these three approaches will be used together. Another important consideration
is what herd performance goal is desired: maximum milk, some amount less
than maximum milk output, maximum milk component production, optimal income over feed costs, minimized purchased feed costs, or some other target.
More than ever, ration formulation software that models rumen fermentation will
be useful such as the Cornell Net Carbohydrate Protein System model, CPMDairy, or the National Research Council model as commonly used examples.
Use of Forages when Corn Grain is Expensive
Forages are typically an economical means of providing nutrients to dairy cattle.
Greater amounts of forage in the diet in place of concentrates will obviously increase the effective fiber content of the diet (unless it is finely processed). The
impact on the digestibility and energy content of the diet will be related to the
digestibility of the fiber in the forage crop.
There are basically two paradigms when feeding forages to dairy cattle: 1) minimal forage in the diet, and 2) maximum forage. Minimal-forage diets are useful
when high quality forage is limited and(or) expensive, whereas maximum-forage
diets will only be successful when high quality (highly digestible) forage is readily available (assuming a highly productive herd is the goal). Fibrous byproducts
are especially useful when high quality forage is limited. These byproducts may
be used as both grain (i.e. starch) and forage NDF replacements.
30
Importance of Forage Quality
Research over many decades has clearly demonstrated the importance of high
quality, high-NDF digestibility forages for optimal milk production. As NDF digestibility of forage increases, researchers have observed the following responses:
·
Greater dry matter intake,
·
Increased milk yield,Higher peak milk yield and greater persistency,
·
Greater milk production efficiency (milk/DMI),
·
Less body weight loss in early lactation,
·
Better body condition, and
·
Improved reproductive performance.
The benefits of feeding diets with higher amounts of digestible NDF include:
·
Increased energy intake,
·
Higher ruminal pH,
·
Increased acetate:propionate and better milk components,
·
No lactic acid and less acidosis risk,
·
Greater bacterial protein production and less need for expensive RUP
supplements,
·
Indigestible NDF interferes with digestion and absorption of starch, protein, and fat, and
·
Constant supply of absorbed nutrients resulting in more milk production.
Several years ago, Michigan State University researchers (Oba and Allen,
1999) reviewed the published literature and developed a relationship between
NDF digestibility and lactational performance. These researchers found that for
every one percentage-unit increase in NDF digestibility, there is a
·
0.44 lb/d increase in dry matter intake
·
0.51 lb/d increase in milk yield
·
0.55 lb/d increase in 4% fat-corrected milk yield
·
0.09 lb/d increase in body weight.
More recently, Washington State University researchers (Johnson et al., 2003)
found that, for high-producing cows (>92 lb/cow/d of milk), each one percentage-unit increase in dry matter digestibility resulted in a 1.41 lb/d/cow increase
in milk production. The bottom line is that seemingly small increases in NDF digestibility can result in highly economical increases in milk yield, body condition,
and reproductive performance. And, remember that greater digestibility reflects
less linking between lignin and cell wall carbohydrates, and a greater ability for
bacteria to colonize and digest forage particles in the rumen.
31
Nonforage Sources of Fiber and Dietary Starch Content
Recent research demonstrates that dietary nonfiber carbohydrate content, and
starch in particular, may be reduced to low concentrations when high amounts
of nonforage fiber sources are fed. Ipharaguerre et al. (2002) fed diets in which
soybean hulls replaced ground corn from 0 to 40% of dietary DM. Corn was reduced from 40.3 to 1% of dietary DM. The dietary NSC (starch and sugars)
ranged from 35.9 to only 15.6% of DM, while the NDF ranged between 26.6 and
45.4%. There were no differences among the diets, from high to low NSC, in
either fat-corrected milk production or DMI.
Boddugari et al. (2001) evaluated diets in which a wet corn gluten feed product
comprised up to 70% of the ration DM (replacing all of the corn grain and 50%
of the forage). The NFC content ranged from 43.2 to 27.0% of DM across two
studies. The efficiency of fat-corrected milk production (FCM/DMI) was similar
for all diets even when the content of NFC was much lower than commonly recommended. These studies were short-term (4-wk periods), and a subsequent
trial evaluated response to a 40% wet corn gluten feed-based diet for the first 63
days in milk (Boddugari et al., 2001). The two diets contained either 43.6 or
35.1% NFC (0 versus 40% wet corn gluten feed product) and the efficiency of
fat-corrected milk production was actually improved from 1.47 to 1.79 for cows
fed the low NFC, low starch diet.
Biologically significant differences exist among the commonly used byproduct
feeds in their carbohydrate fractions. For example, Mills et al. (2002) observed
different lactational responses when either soybean hulls or wet corn gluten
feed replaced corn grain at the same dietary NDF level. We need to keep this in
mind as we incorporate various byproducts into rations. We will lower starch
content, but depending on the byproduct, we will also have variable (and potentially important) effects on other dietary carbohydrate fractions such as sugars,
soluble fiber, and organic acids. But, the two papers cited here clearly demonstrate the effectiveness of low starch, low NFC diets with two byproducts that
vary dramatically in carbohydrate composition (soybean hulls and corn gluten
feed).
Optimal Amounts of Nonforage Fiber Sources for Dairy Cattle
During the past several years, papers have been published that evaluated selected levels of inclusion for several byproducts including wet corn gluten feed,
soybean hulls, brewers grains, and beet pulp, and cottonseed hulls. Few studies
were designed to establish optimal or maximal levels of inclusion in the ration.
Soybean Hulls. A review by Grant (1997) indicated that dietary forage level and
particle size had a large influence on the recommended amount of soybean
hulls to feed to lactating dairy cows. For instance, if dietary forage was >50%
and particle size was adequate, then soybean hulls could be added at ≤25% of
dietary DM. If dietary forage was <50% and particle size was adequate, then
soybean hulls could be added at ≤10% of dietary DM. This paper also indicated
the expected DMI and FCM response to various combinations of forage
amount, particle size, and soybean hull inclusion level based on published literature.
32
More recently, Ipharraguerre et al. (2002) evaluated the effect of various levels
of corn replacement with soybean hulls on ruminal fermentation, nutrient digestion, and lactational performance of midlactation dairy cows. These researchers
evaluated diets containing 26% forage (1:1 alfalfa:corn silage mixture) and pelleted soybean hulls replacing corn in the concentrate to achieve 0, 10, 20, 30, or
40% soybean hulls in the total dietary DM. Dry matter intake decreased linearly
as soybean hulls replaced corn in the concentrate, with the major reduction occurring when soybean hulls provided 30 and 40% of the dietary DM. Production
of 3.5% FCM was not affected by level of soybean hull inclusion in the diet.
Amount of NDF digested was increased, whereas the amount of nonstructural
carbohydrate digested was decreased in the rumen, the lower tract, and in the
total digestive tract as soybean hulls replaced corn grain in the diet. The conclusion of these experiments was that differences in the source of energy (fiber
versus nonstructural carbohydrates), in the amount of fiber and nonstructural
carbohydrate digested, and in the site of digestion in the digestive tract may
cause a shortage of the source and(or) amount of energy that is required for
maximum milk production in high-producing cows when greater than 30% of the
dietary DM is supplied by soybean hulls. In addition, microbial protein production may be negatively impacted when very low amounts of starch and other
nonstructural carbohydrates are fed. Interestingly, these results reinforce research by Nakamura and Owens (1989) who observed a reduction in milk and
milk protein yield as pelleted soybean hulls replaced nearly all of the corn grain
in a total mixed ration containing alfalfa as the sole forage.
Based on this research from Illinois (Ipharraguerre and Clark, 2003), in addition
to the review by Grant (1997), it seems reasonable to conclude that soybean
hulls can replace forage to supply ≤25% of the dietary DM as long as there is
adequate peNDF. Soybean hulls can replace corn grain to supply approximately
30% of the DM in higher grain diets without negatively affecting ruminal fermentation or milk production. Data are still needed to determine maximal levels of
inclusion of soybean hulls in diets for lactating dairy cows. Soybean hulls are
usually competitively priced, and given their nutritional and economical value, it
is reasonable to predict that feeding soybean hulls will increase in the future.
Brewers Grains. Due to their fibrous nature and low energy content, brewers
grains are suitable for dairy cattle to balance consumption of rapidly fermentable
starch. Several recent reports have evaluated the use of wet or dry brewers
grains for dairy cattle. Younker et al. (1998) provided a brief review of research
with brewers grains. In addition, these researchers evaluated the effect of 11.75
or 23.5% dried brewers grains compared with a low and high forage diet; the
brewers grains replaced a portion of the forage, concentrate, or both. These researchers observed that dried brewers grains had slower NDF digestion rates
and faster passage rates than alfalfa. The DMI was depressed by the higher
NDF concentrations in diets in which brewers grains replaced concentrate, although it was a short-term study. Milk fat percentage was reduced for the brewers grains diets, but 4% FCM yield was unaffected by diet. Although dried brewers grains did not appear to be very effective at stimulating milk fat percentage,
DMI was maintained when brewers grains replaced forage, and it appears that
brewers grains can replace a portion of the forage NDF in diets for lactating
dairy cows.
33
In another study conducted at Ohio State University, levels of 8.65, 17.29, or
25.9% wet brewers grains were substituted for alfalfa and corn silages (Firkins
et al., 2002). Dry matter intake and milk production were similar across all diets.
The study showed that, if forage NDF is replaced with byproduct NDF concomitantly with decreasing nonfiber carbohydrates, lactational performance was
similar. The results supported the NRC (2001) minimum forage NDF recommendations. One final study (Dhiman et al., 2003) evaluated dried versus wet
brewers grains at 15% of the ration DM and concluded that lactational performance of dairy cows was similar when diets contained the same DM content.
The bottom line is that it appears that wet or dry brewers grains may be successfully fed to lactating cows at levels up to 25% of ration DM, as long as recommendations for minimal ration forage NDF and nonfiber carbohydrate content
are followed.
Beet Pulp. De Brabander et al. (1999) evaluated the effect of sugar beet pulp in
diets containing either corn silage or grass silage in ratios of either 20:80 or
35:65, DM basis. The chewing indices (eating and ruminating time per unit of
DM ingested) for beet pulp averaged 14.6 min/lb of DM and was little affected
by the nature of the roughage or by the dietary inclusion ratio with forage. Recently, Voelker and Allen (2002) fed diets containing 40% forage and 60% concentrate with either 0, 6.1, 12.1, or 24.3% beet pulp substituted for highmoisture corn on a DM basis. Substituting beet pulp for corn tended to cause a
quadratic response in 3.5% FCM yield with dietary means of 37.5, 38.5, 38.1,
and 36.9 kg/d as level of beet pulp in the diet increased. Treatment did not influence ruminal pH, although DMI decreased linearly with increasing beet pulp in
the diet. Because of more extensive fiber digestion as dietary beet pulp increased, total tract DM digestibility tended to increase, and therefore consumption of digestible DM was unaffected. Partial substitution of high-fiber beet pulp
for high-starch, high-moisture corn improved milk production by increasing NDF
digestibility without reducing total tract starch digestion.
Cottonseed Hulls. Cottonseed hulls are a byproduct of cotton processing, contain a large amount of NDF and associated lignin, and have been considered a
useful source of nonforage fiber when forage supplies are limited. Inclusion of
cottonseed hulls in lactation rations has resulted in increased DMI, higher ruminal pH, and decreased NDF and DM digestibility in the total tract (Akinyode et
al., 2000). Kononoff and Heinrichs (2003) evaluated the effect of including cottonseed hulls at 0 or 8% of the dietary DM on performance of early lactation
dairy cows. The mean particle length of the diet decreased with inclusion of cottonseed hulls, and DMI increased. However, total chewing time was unaffected,
although eating and ruminative efficiency (minutes per unit of NDF intake) decreased with inclusion of cottonseed hulls. Milk production did not differ among
diets, but inclusion of cottonseed hulls improved yield of milk protein.
34
Corn Milling Co-Products. There are two types of grain milling: dry and wet
milling. Wet milling uses grain for production of ethanol, sweetener, and other
products with the major feed byproducts being corn gluten feed (wet or dry)
and steep liquor. Dry milling uses grain for production of ethanol and carbon
dioxide with the major feed byproducts being distillers grains plus solubles (wet
or dry) and distillers solubles (corn syrup). Byproducts of wet and dry milling,
most notably distillers grains (DG) and corn gluten feed (CGF), have been
used as forage and concentrate replacements in diets for lactating dairy cattle.
Commonly, DG and CGF are fed at less than 20% of the dietary dry matter, but
recent research indicates that substantially more can be fed. Optimizing the
use of these ethanol byproducts in ruminant diets will become increasingly important as more ethanol plants are built in the next decade. An understanding
of the chemical composition of these grain milling byproducts enables us to
effectively position them in dairy formulations. Both DG and CGF contain 35 to
45% NDF that is highly digestible (6 to 8%/h digestion rate) due to low lignification and can therefore replace starch and reduce the risk of ruminal acidosis
(Allen and Grant, 2000). Due to their small particle size, both co-products have
less than 15% physically effective NDF and so do not stimulate much rumination. Consequently, particle size of dietary forage is a critical issue when either
byproduct replaces forage.
Major compositional differences between DG and CGF include lipid and protein
fractions (Schingoethe, 2005). Distillers grains, wet or dry, contain 30 to 35%
crude protein (CP), of which approximately 50 to 55% is ruminally undegradable protein (RUP). In contrast, CGF contains 20 to 25% CP and only 25 to
30% RUP. The lipid content of DG ranges between 10 and 15%, but is less
than 3% for CGF. These differences in physicochemical properties have positioned CGF primarily as a source of digestible fiber, whereas DG have been
positioned as a source of RUP. Substantial variability in chemical composition
of DG among ethanol plants continues to be a challenge when feeding DG to
dairy cattle. Most recently, Kleinschmit et al. (2005) found that the rumen undegradability of protein from dried DG ranged from 56.5 to 78.0% across five
ethanol plants. The RUP content of wet and dry DG was greater than soybean
meal, and dried DG had greater RUP than wet DG. Intestinal digestibility of DG
from these same five plants ranged from 62.5 to 77.4%. Processing differences
among ethanol plants may significantly influence the nutritional value of DG for
dairy cattle.
Distillers Grains. The primary feed byproduct from ethanol production is DG
or more commonly DG plus solubles. In this article, the abbreviation DG refers
to distillers grains plus solubles. Numerous studies have evaluated the impact
of DG on dry matter intake and milk response of dairy cattle and the reader is
referred to comprehensive summaries published by Chase (1991) and more
recently by Schingoethe (2005). In the experiments summarized by Schingoethe (2005), most studies found that lactational performance was similar, or
occasionally greater, for cows fed DG compared with soybean meal. Darker
DG products reflected possible heat damage and consequently resulted in reduced milk production response.
35
Most research has focused on DG as an alternative protein source to soybean
meal [(Owen and Larson, 1991) as an example]. Distillers grains provide a
good source of RUP with reported values ranging from about 45 to 55%. Although the RUP content of dry DG is slightly higher than wet DG, the difference
is usually small (47% RUP for wet versus 54% RUP for dry DG). If the RUP
content of dry DG is higher than average, then an analysis for heat damage
should be done.
Schingoethe (2005) suggested a maximum of 20% DG in the dietary dry matter
fearing potential palatability problems and excessive protein consumption above
this amount. However, a recent experiment (Schingoethe at al., 1999) found
that diets containing 31.2% wet corn DG versus a control diet (corn and soybean meal-based) resulted in a 13.6% increase in efficiency of energy-corrected
milk production. The forage component of these diets contained approximately
63% corn silage and 37% alfalfa hay and resulted in a total dietary CP content
of 21% with a reported 22% elevation of serum urea levels. A long-term nutritional consideration when feeding high levels of DG (greater than 20% of dietary
dry matter) would be the proper ratio of forage sources to reduce dietary crude
protein content to avoid excessively high serum urea nitrogen levels.
Another consideration when feeding higher levels of DG would be supplemental
sources of lysine if corn silage comprises the majority of the forage, and if corn
grain is also fed, because corn proteins are limiting in lysine content relative to
the requirement for milk protein production. Previous research has demonstrated that lysine is limiting to milk production when DG are fed in corn-based
diets for lactating dairy cows. Nichols et al. (1998) found that when diets containing 20% corn DG were supplemented with ruminally protected lysine and
methionine, milk yield and milk protein yield increased because the diet was deficient in lysine.
Distillers grains also are an excellent source of energy due to their high content
of digestible NDF and lipid. Estimates of the energy content of corn DG from
research with growing beef cattle range from 83 to 169% that of corn grain
[cited in (Birkelo et al., 2004)]. Comparatively little research has attempted to
measure the energy content of DG for lactating dairy cattle. Birkelo et al. (2004)
measured the energy balance of lactating dairy cattle fed diets containing 31.2%
wet DG or a combination of rolled corn and soybean meal. The diet containing
wet DG had a greater net energy content than a diet with rolled corn and soybean meal because of the higher lipid content of wet DG. Energy estimates for
wet DG were 10 to 15% greater than those reported for dried corn DG by the
National Research Council (2001).
There is evidence that the lipid in corn DG is effective at increasing the unsaturated fatty acid content of milk fat (Schingoethe et al., 1999). Diets for dairy
cows that contain approximately 30% DG would provide about 0.5 kg/d additional lipid depending on the milling process for the ethanol plant. If feeding the
DG byproduct could result in improvements in the unsaturated fatty acid content
of milk fat, there would be benefits for processing, human health, and marketability of dairy products (Schingoethe, 2005). Schingoethe et al. (1999) found
that diets containing 31.4% corn DG increased the proportion of desirable unsaturated fatty acids in milk fat without changing overall milk fat production.
36
One practical concern when feeding high levels of DG to dairy cattle is the potential to reduce milk fat output. Depending on the lipid content of the DG product, diets containing 20 to 30% DG may contribute substantial amounts of lipid
to the diet. Adding DG in place of low fat, low fiber concentrates will increase
dietary oil content which could reduce milk fat secretion. But, adding DG will
also increase dietary fiber content which can increase milk fat content.
Leonardi et al. (2005) fed diets containing 28% NDF with DG added at a level
(15% of dietary dry matter) to bring total fatty acids up to 5% of the dietary dry
matter. Under these dietary conditions, milk and milk protein yield increased
with no reduction in milk fat yield. Reduced proportions of shorter chain fatty
acids and increased proportions of longer chain fatty acids in milk fat suggested
that de novo fatty acid synthesis in the mammary gland was inhibited, but this
was offset by greater secretion of long chain fatty acids from the diet.
Wet versus Dry Distillers Grains. Two major considerations when using wet or
dry DG are handling issues and cost of the byproduct. Dried DG can be stored
for long periods of time, can be more readily transported, and can be more easily blended with other ingredients than wet DG. But, feeding wet DG avoids the
cost associated with drying the byproduct. Additionally, wet DG will not remain
fresh and palatable for much longer than 5 to 7 days (Schingoethe, 2005).
Al-Suwaiegh et al. (2002) compared wet versus dry DG from the fermentation of
either 100% corn or 100% sorghum grains. All the diets contained 50% of a 1:1
mixture of alfalfa and corn silages and 15% DG. Chemical composition of the
corn and sorghum DG were similar. Efficiency of fat-corrected milk production
was similar for cows fed either corn or sorghum DG in the wet or dry form. Because efficiency of milk production was the same, whether wet or dry, the form
of DG is primarily a function of what works best for the farm given the feed storage and handling capabilities. The production of fat-corrected milk tended to be
reduced when cows were fed DG from sorghum versus corn. The impact of
grain source on the quality of DG and its effect on long-term milk production is
unknown.
More recently, Ladd et al. (2005) compared wet versus dry DG at either 10 or
20% of the dietary dry matter. Feed intake tended to be greater for cows fed the
control diet without DG, and milk yield was greater for cows fed DG, resulting in
more efficient production of milk for cows fed the diets containing DG. Whether
DG was fed at 10 or 20% of the diet had no impact on cow response. Feeding
wet DG instead of dry DG increased milk fat and protein percentages but not
yield.
Recent Research with Cottonseed Byproducts
During the past five years, more research has been published on feeding cottonseed byproducts to dairy cattle than any other byproduct or alternative feed.
Several papers have been published concerning feeding cottonseed products
and gossypol content (Blackwelder et al., 1998; Velasquez-Pereira et al., 1999;
Noftsger et al., 2000; Mena et al., 2001; Santos et al., 2002), but review of this
topic is outside the scope of this paper.
37
Several papers have evaluated the peNDF value of whole cottonseed. Mooney
and Allen (1997) found that the physically effectiveness of NDF from whole cottonseed was 50% of long-cut alfalfa and 127% of short-cut alfalfa silage NDF.
These researchers pointed out that the peNDF values for any byproduct will be
relative to the “standard” forage they’re measured against. Harvatine et al.
(2002) found that, based on chewing activity, the NDF from whole cottonseed
was 84% as effective as NDF from alfalfa silage. It seems clear that the peNDF
value of whole cottonseed is nearly similar to alfalfa silage depending on the
particle size of the silage itself. Lima et al. (2003) observed that the presence of
linters on cottonseed had no effect on chewing effectiveness, an observation
also made by Moreira et al. (2003) who noted no difference in productive response for multi- and primiparous cows fed either linted or delinted whole cottonseed.
Although not reviewed here, several recent papers have examined the effects of
mechanical processing and coating technologies on the feeding value and handling characteristics of whole cottonseed (Bernard and Calhoun, 1997; Bernard,
1999; Bernard et al., 1999; Meyer et al., 2001).
Creative Combinations of Byproducts
An understanding of the physicochemical characteristics of byproducts feeds
enables us to effectively position them in dairy formulations. For example, soybean hulls have desirable properties to mix with liquid byproducts; wet distillers
grains and corn gluten feed ought to complement each other well, and combinations of oilseeds, their lipid byproducts, and fibrous byproducts may hold promise as means to produce designer milk products with desirable fatty acid profiles. We need to understand, at a minimum, how the CP, ruminally undegraded
protein, lipid, and peNDF content position various byproducts, or combinations,
in dairy diets designed to optimize or maximize byproduct inclusion.
Several recent research reports have evaluated the possibility of using dry, fibrous byproducts as a carrier for liquid byproducts. Kansas State researchers
(DeFrain et al., 2002a, b) examined a combination of raw soybean hulls and
condensed corn steep liquor as a feed supplement for lactating dairy cows. The
product was comprised of 75% soybean hulls and 25% steep liquor on a dry
basis and contained 24.2% CP, 8.7% ruminally undegraded protein, 28.9%
ADF, 36.7% NDF, and 2.5% ether extract. The diets were control, pelleted soybean hulls at 14.3% of dietary DM, and the mixture replacing 6.2% alfalfa hay,
3.7% corn silage, 6.6% corn, and 3.3% soybean meal for a total of 20.7% replacement in the diet. Feeding the pelleted soybean hulls or the mixture of soybean hulls and steep liquor improved energy-corrected milk above the control
diet. In another study (DeFrain et al., 2002b), this same research group found
that the soybean hull and steep liquor product did not reduce the severity of pH
and volatile fatty acid response to an induced subacute ruminal acidosis challenge in lactating dairy cows.
38
Dietary Starch to Fiber Ratio
Recently, Beckman and Weiss (2005) published a paper that evaluated whether
increasing dietary NDF:starch ratio influenced NDF digestibility when diets were
formulated to have similar NDF digestibility. All diets contained 41.5% corn silage (DM basis), but content of corn varied between 23.3 and 34.8% with
NDF:starch ratios of 0.74, 0.95, and 1.27. A soybean hull:cottonseed hull mixture (54% soyhulls and 46% cottonseed hulls) which had the same NDF digestibility as the forage NDF was substituted for the corn grain in varying proportions
to obtain the desired NDF:starch ratios. Starch content of these diets varied
from 25.4 to 33.3% and NDF varied between 24.7 and 32.2.
Intake tended to increase as NDF:starch ratio increased and total tract DM and
energy digestibility decreased. However, NDF digestibility was not influenced by
NDF:starch ratio. Greater DMI appeared to compensate for reduced digestible
energy content such that energy intake was similar among the diets. This study
demonstrated that NDF digestibility may be less sensitive to increases in the
starch:NDF ratio under carefully controlled experimental conditions. Practically,
there is almost always complete confounding of NDF and starch content and the
animal response is a composite response to all the carbohydrate fractions. Dietary formulation approaches that allow greater use of highly digestible NDF from
byproduct feeds (replacing either forage or concentrate) represent a strategy for
feeding either high or low starch diets and obtaining desirable lactational performance.
Altering Rate and Site of Starch Digestion with Co-Products
Recent research with dairy cows indicates that some co-product feeds may not
only reduce the amount of starch fermented in the rumen when substituted for
grain, but also will reduce the ruminal digestibility of the remaining starch (Allen,
2003). Ipharraguerre et al. (2002) substituted soybean hulls for dry ground corn
at 0, 10, 20, 30, and 40% of dietary dry matter and observed that ruminal digestibility of nonstructural carbohydrates tended to decrease linearly from nearly
30% to less than 5% without reducing ruminal or total tract organic matter digestibility.
Voelker and Allen (2002) reported similar responses when pelleted beet pulp
was substituted for high moisture corn at 0, 6, 12, and 24% of dietary dry matter. The amount of starch truly digested in the rumen decreased markedly from
3.8 to 0.7 kg/d, partly because of the expected reduction in starch intake from
lower dietary starch content, but also from an unexpected reduction in true ruminal starch digestibility from 47% to 17% as beet pulp replaced high moisture
corn. There was no effect of diet on total tract starch digestion despite this large
reduction in ruminal starch digestibility due to compensatory postruminal starch
digestion. Also, organic matter digestibility in the rumen was not affected because of increased NDF digestion as beet pulp replaced corn. The reduction in
ruminal starch digestibility was because rate of ruminal starch digestion decreased from 11.3 to 1.7%/h and rate of starch passage from the rumen increased from 15.9 to 23.5%/h.
39
Also, organic matter digestibility in the rumen was not affected because of increased NDF digestion as beet pulp replaced corn. The reduction in ruminal
starch digestibility was because rate of ruminal starch digestion decreased from
11.3 to 1.7%/h and rate of starch passage from the rumen increased from 15.9
to 23.5%/h.
Currently, it is unknown if other nonforage sources of fiber have similar effects
on rates of digestion and passage from the rumen. It deserves further investigation because of the potentially important implications for limiting ruminal starch
digestion. It is possible that substitution of starch with by-product feeds could be
an effective method for manipulating ruminal starch digestion. Substitution of
nonforage fiber sources for both forage and grain may be needed to limit diet
fermentability as forage content is reduced.
Interaction of Forage and Nonforage Fiber Sources
Fibrous particles have a high probability for escape from the rumen due to their
small particle size and high specific gravity. They are rapidly fermented and so
are less buoyant. Because most nonforage sources of fiber do not stimulate rumination as effectively as coarse forages, dietary forage must have adequate
particle length for normal rumination when significant amounts of forage fiber
are replaced with nonforage fiber. Additionally, forage of longer particle length
forms a digesta mat that more effectively filters and entangles smaller particles
(such as byproducts and fine forage particles) allowing greater time for fermentation in the rumen.
Nebraska researchers evaluated the effect of ruminal mat consistency on passage and digestion of wet corn gluten feed in lactating dairy cows (Allen and
Grant, 2000). Diets were formulated to contain approximately 40% alfalfa, 24%
wet corn gluten feed, plus a corn and soybean meal-based concentrate. One
diet contained alfalfa silage and the other contained a 1:1 blend of alfalfa silage
and coarsely chopped alfalfa hay of similar quality to increase particle size.
Cows fed the diet with added hay and wet corn gluten feed had greater rumination activity and ruminal mat consistency, a 35% reduction in passage rate of
corn gluten feed, 40% greater ruminal NDF digestion, and 6% more milk production. Earlier research has demonstrated the same positive effect with soybean hulls (Weidner and Grant, 1994). The bottom line is that adequate forage
particle length and a well-formed ruminal digesta mat will not only promote cow
health, but will slow passage of byproducts and allow more complete ruminal
NDF digestion and greater productivity.
40
Selected References
Abel-Caines, S. F., R. J. Grant, and S. G. Haddad. 1997. Whole cottonseeds or
a combination of soybeans and soybean hulls in the diets of lactating dairy
cows. J. Dairy Sci. 80:1353-1357.
Akinyode, A. M., M. B. Hall, C. R. Staples, H. H. Head, and W. E. Kunkle. 2000.
Effects of cottonseed hulls in the diets of dairy cows. J. Dairy Sci. 83:296
(Abstr.).
Allen, D. M., and R. J. Grant. 2000. Interactions between forage and wet corn
gluten feed as sources of fiber in diets for lactating dairy cows. J. Dairy Sci.
83:322-331.
Allen, M. S. 2003. Forage alternatives. Page 101 in Proc. Tri-State Dairy Nutr.
Conf. April 8-9, 2003. Fort Wayne, IN.
Al-Suwaiegh, S., K. C. Fanning, R. J. Grant, C. T. Milton, and T. J. Klopfenstein.
2002. Utilization of distillers grains from the fermentation of sorghum or corn in
diets for finishing beef and lactating dairy cattle. J. Anim. Sci. 80:1105-1111.
Bernard, J. K. 1999. Performance of lactating dairy cows fed whole cottonseed
coated with gelatinized cornstarch. J. Dairy Sci. 82:1305-1309.
Bernard, J. K., and M. C. Calhoun. 1997. Response of lactating dairy cows to
mechanically processBernard, J. K., M. C. Calhoun, and S. A. Martin. 1999. Effect of coating whole cottonseed on performance of lactating dairy cows. J.
Dairy Sci. 82:1296-1304.
Birkelo, C. P.; Brouk, M. J.; Schingoethe, D. J. 2004. The energy content of wet
corn distillers grains for lactating dairy cows. J. Dairy Sci. 87:815-1819.
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1998. Milk production and plasma gossypol of cows fed cottonseed and oilseed
meals with or without rumen-undegradable protein. J. Dairy Sci. 81:2934-2941.
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of forage and concentrate with a new wet corn milling product for lactating dairy
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Clark, P. W., and L. E. Armentano. 1993. Effectiveness of neutral detergent fiber in whole cottonseed and dried distillers grains compared with alfalfa haylage. J. Dairy Sci. 76:2644-2652.
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Bouque. 1999. Evaluation of the physical structure of fodder beets, potatoes,
pressed beet pulp, brewers grains, and corn cob silage. J. Dairy Sci. 82:110121.
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DeFrain, J. M., J. E. Shirley, E. C. Titgemeyer, A. F. Park, and R. T. Ethington.
2002a. A pelleted combination of raw soyhulls and condensed corn steep liquor
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Dhiman, T. R., and H. R. Bingham, and H. D. Radloff. 2003. Production response of lactating cows fed dried versus wet brewers grain in diets with similar
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42
Mena, H. J.E.P. Santos, J. T. Huber, J. M. Simas, M. Tarazon, and M. C. Calhoun. 2001. The effects of feeding varying amounts of gossypol from whole cottonseed and cottonseed meal in lactating dairy cows. J. Dairy Sci. 84:22312239.
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2001. Effect of mechanical processing and fat removal on the nutritive value of
cottonseed for lactating dairy cows. J. Dairy Sci. 84:2503-2514.
Mooney, C. S., and M. S. Allen. 1997. Physical effectiveness of the neutral detergent fiber of whole linted cottonseed relative to that of alfalfa silage at two
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Effect of whole and expanded-expelled cottonseed on milk yield and blood gossypol. J. Dairy Sci. 83:2539-2447.
Oba, M., and M.S. Allen. 1999. Evaluation of the importance of the digestibility
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Schroeder, J. W. 2003. Optimizing the level of wet corn gluten feed in the diet of
lactating dairy cows. J. Dairy Sci. 86:844-851.
VanBaale, M. J., J. E. Shirley, E. C. Titgemeyer, A. F. Park, M. J. Meyer, R. U.
Lindquist, and R. T. Ethington. 2001. Evaluation of wet corn gluten feed in diets
for lactating dairy cows. J. Dairy Sci. 84:2478-2485.
Voelker, J. A., and M. S. Allen. 2002. Effects of level of substation of pelleted
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Dairy Sci. 81:2645-2656.
43
The Impact of Heat Stress on Nutrient Partitioning and Dairy Production
L.H. Baumgard and R.P. Rhoads
Department of Animal Sciences
The University of Arizona
Heat stress negatively impacts a variety of dairy parameters including milk
yield and reproduction and therefore is a significant financial burden (~$900 million/year in the USA; St. Pierre et al., 2003) in many dairy-producing areas of
the world. Advances in management (i.e. cooling systems; Armstrong, 1994;
VanBaale et al., 2005) and nutritional strategies (West, 2003) have alleviated
some of the negative impact of thermal stress on dairy cattle, but production
continues to decrease during the summer. The accurate identification of heatstressed cows and a thorough understanding of the biological mechanism(s) by
which thermal stress reduces milk synthesis and reproductive indices is critical
for developing novel approaches (i.e. genetic, managerial and nutritional) to
maintain production or minimize the reduction in dairy cow productivity during
stressful summer months.
BIOLOGICAL CONSEQUENCE OF HEAT STRESS
The biological mechanism by which heat stress impacts production and reproduction is partly explained by reduced feed intake, but also includes altered
endocrine status, reduction in rumination and nutrient absorption, and increased
maintenance requirements (Collier and Beede, 1985; Collier et al., 2005) resulting in a net decrease in nutrient/energy availability for production. This decrease in energy intake results in a reduction in energy balance (EBAL), and
partially explains (reduced gut fill also contributes) why cows lose significant
amounts of body weight when subjected to heat stress.
Heat stress causes reduced energy intake in most, if not all, of lactating
cows resulting in negative energy balance (NEBAL), and this is likely stage of
lactation independent. Reductions in feed and energy intake predispose the
dairy cow to a bioenergetic state, similar (but not to the same extent) to the NEBAL observed in early lactation. The NEBAL associated with the early postpartum period is coupled with increased risk of metabolic disorders and health
problems (Goff and Horst, 1997; Drackley, 1999), decreased milk yield and reduced reproductive performance (Lucy et al., 1992; Beam and Butler, 1999;
Baumgard et al., 2002; 2006). It is likely that many of the negative effects of
heat stress on production, animal health and reproduction indices are mediated
by the reduction in EBAL (similar to the way it is during the transition period).
However, it is not clear how much of the reduction in performance (milk yield
and reproduction) can be attributed or accounted for by the biological parameters affected by heat stress (i.e. reduced feed intake vs. increased maintenance
costs).
44
HEAT STRESS AND RUMEN HEALTH
Heat stress has long been known to adversely affect rumen health. One
way cows dissipate heat is via panting and this increased respiration rate results
in enhanced CO2 (carbon dioxide) being exhaled. In order to be an effective
blood pH buffering system, the body needs to maintain a 20:1 HCO3(bicarbonate) to CO2 ratio. Due to the hyperventilation induced decrease in
blood CO2, the kidney secretes HCO3- to maintain this ratio. This reduces the
amount of HCO3- that can be used (via saliva) to buffer and maintain a healthy
rumen pH. In addition, panting cows drool and drooling reduces the quantity of
saliva that would have normally been deposited in the rumen. Furthermore, due
to reduced feed intake, heat-stressed cows ruminate less and therefore generate less saliva. The reductions in the amount of saliva produced and salivary
HCO3- content and the decreased amount of saliva entering the rumen make
the heat stressed cow much more susceptible to sub-clinical and acute rumen
acidosis (see review by Kadzere et al., 2002).
When cows begin to accumulate heat, there is a redistribution of blood to
the extremities in an attempt to dissipate internal energy. As a consequence,
there is reduced blood flow to the gastrointestinal track and nutrient uptake may
be compromised (McGuire et al., 1989). Therefore, fermentation end products
(volatile fatty acids) probably accumulate and contribute to the reduced pH.
Due to the reduced feed intake caused by heat stress and the heat associated with fermenting forages, nutritionists typically increase the energy density
of the ration. This is often accomplished with extra concentrates and reductions
in forages. However, this needs to be conducted with care as this type of diet
can be associated with a lower rumen pH. The combination of a “hotter” ration
and the cows reduced ability to neutralize the rumen (because of the reduced
saliva HCO3- content and increased drooling) directly increases the risks of rumen acidosis and indirectly enhances the risk of negative side effects of an unhealthy rumen (i.e. laminitis, milk fat depression, etc.).
METABOLIC ADAPTATIONS TO REDUCED FEED INTAKE
A prerequisite of understanding the metabolic adaptations which occur with
heat stress, is an appreciation of the physiological and metabolic adaptations to
thermal-neutral NEBAL (i.e. underfeeding or during the transition period).
45
The early lactation dairy cow is a prime example of an animal that cannot
consume enough feed to meet maintenance and milk production costs and
negative energy balance ensues (Moore et al., 2005a). Negative energy balance is associated with a variety of metabolic changes that are implemented to
support the dominant physiological condition of lactation (Bauman and Currie,
1980). Marked alterations in both carbohydrate and lipid metabolism ensure
partitioning of dietary derived and tissue originating nutrients towards the mammary gland, and not surprisingly many of these changes are mediated by endogenous somatotropin which is naturally increased during periods of NEBAL
(Bauman and Currie, 1980). One classic response is a reduction in circulating
insulin coupled with a reduction in systemic insulin sensitivity. The reduction in
insulin action allows for adipose lipolysis and mobilization of non-esterified fatty
acids (NEFA; Bauman and Currie, 1980). Increased circulating NEFA are typical in “transitioning” cows and represent (along with NEFA derived ketones) a
significant source of energy (and are precursors for milk fat synthesis) for cows
in NEBAL. Post-absorptive carbohydrate metabolism is also altered by the reduced insulin action during NEBAL with the net effect of reduced glucose uptake by systemic tissues (i.e. muscle and adipose). The reduced nutrient uptake coupled with the net release of nutrients (i.e. amino acids and NEFA) by
systemic tissues are key homeorhetic (an acclimated response vs. an acute/
homeostatic response) mechanisms implemented by cows in NEBAL to support
lactation (Bauman and Currie, 1980). The thermal-neutral cow in NEBAL is metabolically flexible, in that she can depend upon alternative fuels (NEFA and ketones) to spare glucose, which can be utilized by the mammary gland to copiously produce milk.
HEAT STRESS AND PRODUCTION VARIABLES
Heat stress reduces both feed intake and milk yield and the decline in nutrient intake has been identified as a major cause of reduced milk synthesis
(Fuquay, 1981). However, the exact contribution of declining feed intake to the
overall reduced milk yield remains unknown. To evaluate this question, we utilized a group of thermal neutral pair-fed animals to eliminate the confounding
effects of nutrient intake. Lactating Holstein cows in mid-lactation were either
cyclically heat-stressed (THI = ~80 for 16 hrs/d) for 9 days or remained in constant thermal neutral conditions (THI = ~ 64 for 24 hrs/d) but pair-fed with heatstressed cows to maintain similar nutrient intake. Cows were housed at the University of Arizona’s ARC facility and individually fed ad libitum a TMR consisting
primarily of alfalfa hay and steam flaked corn to meet or exceed nutrient requirements (NRC, 2001). Heat-stressed cows had an average rectal temperature of
~105° F during the afternoons of the treatment implementation. Heat-stressed
cows had an immediate reduction (~5 kg/d) in dry matter intake (DMI) with the
decrease reaching nadir at ~ day 4 and remaining stable thereafter (Figure 1).
As expected and by design, thermal-neutral pair-fed cows had a feed intake pattern similar to heat stressed cows (Figure 1). Heat stress reduced milk yield by
~14 kg/d with production steadily declining for the first 7 days and then reaching
a plateau (Figure 2). Thermal neutral pair-fed cows also had a reduction in milk
yield of approximately 6 kg/d, but milk production reached its nadir at day 2 and
remained relatively stable thereafter (Figure 2). This indicates the reduction in
DMI can only account for ~40-50% of the decrease in production when cows
are heat-stressed and that ~50-60% can be explained by other heat-stressed
induced changes.
46
METABOLIC ADAPTATIONS TO HEAT STRESS
Estimating EBAL during heat stress introduces problems independent of those
that are inherent to normal EBAL estimations (Vicini et al., 2002). Considerable
evidence suggest increased maintenance costs are associated with heat stress
(7 to 25%; NRC, 2001), however due to complexities involved in predicting upper critical temperatures, no universal equation is available to adjust for this increase in maintenance (Fox and Tylutki, 1998). Maintenance requirements are
increased, as there is a large energetic cost of dissipating stored heat. Not incorporating a heat stress correction factor results in overestimating EBAL and
thus inaccurately predicting energy status.
Heat Stress
Underfed
25
DMI (kg/d)
20
15
10
5
1
2
3
4
5
6
7
8
9
Day
Figure 1. Effects of heat stress and pair-feeding thermal neutral lactating Holstein cows on dry matter intake. Rhoads et al., 2007
47
Heat Stressed
50
Under Fed
Milk Yield (kg/d)
45
40
35
30
25
20
0
1
2
3
4
5
6
7
8
9
Day
Figure 2. Effects of heat stress and pair-feeding thermal neutral conditions on
milk yield in lactating Holstein cows. Rhoads et al., 2007
48
Due to the reductions in feed intake and increased maintenance costs, and
despite the decrease in milk yield heat stressed cows enter into a state of NEBAL (Moore et al., 2005b). In a similar trial as to the one described above,
heat-stressed cows entered into NEBAL (~4-5 Mcal/d) and remained at that
level for the entire duration of heat stress (Figure 3; Wheelock et al., 2006).
However, unlike NEBAL in thermal neutral conditions, heat-stressed induced
NEBAL doesn’t result in elevated plasma NEFA (Figure 4). This was surprising
as circulating NEFA are thought to closely reflect calculated EBAL (Bauman et
al., 1988). In addition, using an intravenous glucose tolerance test, we demonstrated that glucose disposal (rate of cellular glucose entry) is greater in heatstressed compared to thermal neutral pair-fed cows (Figure 5; Wheelock et al.,
2006). Furthermore, heat-stressed cows have a much greater insulin response
to a glucose challenge when compared to underfed cows (data not presented).
Both the aforementioned changes in plasma NEFA and metabolic/hormonal adjustments in response to a glucose challenge can be explained by increased
insulin effectiveness. Insulin is a potent antilipolytic signal (blocks fat break
down) and the primary driver of cellular glucose entry. The apparent increased
insulin action causes the heat-stressed cow to be metabolically inflexible, in that
she does not have the option to oxidize fatty acids and ketones. As a consequence, the heat-stressed cow becomes increasingly dependant on glucose for
her energetic needs and therefore less glucose is directed towards the mammary gland.
As stated earlier, the NRC (2001) arbitrarily indicates that mild to severe
heat stress will increase maintenance requirements by 7 to 25% but indicates,
“insufficient data are currently available to quantify these effects accurately”. A
typical lactating dairy cow will have a maintenance requirement of 9.7 Mcal/d (or
0.08 Mcal/kg BW 0.75; NRC, 2001). In our experiment, ~8 kg of milk/d could not
be explained by the reduction in feed intake (Figure 1 and 2) and this has an
energetic value of approximately 6.1 Mcal/d (or 63% of daily maintenance requirements for a thermal neutral animal). If all of the difference in milk synthesis (~8 kg/d) could be explained by the increase in maintenance requirements
then heat-stressed cows would have an increase in maintenance requirements
of 63%. However, we are currently unable to identify how much of the 8 kg of
milk can be explained by elevated maintenance needs, but if 25, 50 and 75% of
the 6.1 Mcal/d was in fact utilized for increased maintenance, it would represent
a 16, 31 and 47% increase in maintenance requirements, respectively. Deciphering how much of the milk yield differential can be explained by increased
maintenance costs vs. other altered biological systems (i.e. reduced nutrient
absorption, altered endocrine status etc.) is of primary interest.
49
Well-fed ruminants primarily oxidize (utilize) acetate (a rumen produced volatile
fatty acid) as their principal energy source. However, during NEBAL cows also
largely depend on NEFA for energy. Therefore, it appears the post-absorptive
metabolism of the heat-stressed cow markedly differs from a thermal-neutral
counterpart, despite similar negative energetic states. The apparent switch in
metabolism and the increase in insulin sensitivity may be a mechanism by
which cows decrease metabolic heat production, as oxidizing glucose is more
efficient (Baldwin et al., 1980). In vivo glucose oxidation yields 38 ATP
(assuming the DG of ATP hydrolysis is -12.3 kcal/mole under cellular conditions; Berg et al., 2007) or 472.3 kcal of energy (compared to 637.1 kcal in a
bomb calorimeter) and in vivo fatty acid oxidation (i.e. stearic acid) generates
146 ATP or 1814 kcal of energy (compared to 2697 kcal in a bomb calorimeter).
Despite having a much greater energy content, due to differences in the efficiencies of capturing ATP, oxidizing fatty acids generates more metabolic heat
(~2 kcal/g or 13% on an energetic basis) compared to glucose. Therefore, during heat stress, preventing or blocking adipose mobilization/breakdown and increasing glucose “burning” is presumably a strategy to minimize metabolic heat
production.
Treatment Initiation
EBAL (Mcal/d)
6
4
Heat Stress
Underfed
2
0
-2
-4
-6
-8
0
7
14
21
Day
Figure 3. Effects of heat stress and pair-feeding thermal neutral conditions on
calculated net energy balance in lactating Holstein cows. Adapted from Wheelock et al., 2006.
50
The mammary gland requires glucose to synthesize milk lactose and lactose
production is the primary osmoregulator and determinant of milk volume.
However, in an attempt to generate less metabolic heat, the body (primarily
skeletal muscle) appears to utilize glucose at an increased rate. As a
consequence, the mammary gland may not receive adequate amounts of
glucose and thus mammary lactose production and subsequent milk yield is
reduced. This may be the primary mechanism which accounts for the additional
reductions in milk yield that cannot be explained by decreased feed intake
(Figures 1 and 2).
In addition to heat-stressed cows requiring special attention with regards to
heat abatement and other dietary considerations (i.e. concentrate:forage ratio,
HCO3- etc.) they may also have an extra requirement for dietary or rumenderived glucose precursors. Of the three main rumen-produced volatile fatty
acids, propionate is the one primarily converted into glucose by the liver. Highly
fermentable starches such as grains increase rumen propionate production, and
although propionate is the primary glucose precursor, feeding additional grains
can be risky as heat-stressed cows are already susceptible to rumen acidosis.
NEFA
500
Heat Stress
Under Feeding
450
uEq/ml
400
350
300
250
200
150
100
0
2
4
6
8
10
Day
Figure 4. Effects of heat stress and pair-feeding thermal neutral conditions
on circulating non-esterified fatty acids (NEFA) in lactating Holstein cows.
Adapted from Wheelock et al., 2006.
51
Glucose (mg/dl)
225
Heat Stressed
Underfed
175
125
75
25
-40
-20
0
20
40
60
80
100
Time (min)
Figure 5. Effects of heat stress and pair-feeding thermal neutral conditions on
plasma glucose response to a glucose challenge. Adapted from Wheelock et
al., 2006.
52
PRACTICAL SOLUTIONS
Water: Clearly, water intake is vital for milk production (milk is ~90% water) but
it is also essential for thermal homeostasis. In contrast to common
perception, heat-stressed cows remain well-hydrated (via large
increases in water consumption) and actually may become
hyperhydrated (McDowell et al., 1969; Schneider et al., 1988, O’Brien
and Baumgard, unpublished data). This illustrates how important water
availability and waterer/tank cleanliness becomes during the summer
months. Keeping water tanks clear of feed debris and algae is a simple
and inexpensive strategy to help cows remain cool.
Rumen Health: As explained earlier, the heat-stressed cow is prone to rumen
acidosis and many of the lasting effects of warm weather (laminitis, low
milk fats etc.) can probably be traced back to a low rumen pH during the
summer months. As a consequence, care should be taken when feeding
“hot” rations during the summer months. In addition, fiber quality is an
important consideration year around, but it is paramount during the
summer as it has some buffering capacity and stimulates saliva
production. Furthermore, dietary HCO3- may be a valuable tool to
maintain a healthy rumen pH although there is some academic
controversy regarding the effectiveness of this dietary supplement.
Fat: Despite the fact that it appears heat-stressed cows do not prefer to oxidize
body reserves for energy, feeding dietary fat (rumen inert/rumen bypass)
probably remains an effective strategy of providing extra (and safe with
regards to rumen health) energy during a time of negative energy
balance. Compared to starch and fiber, fat has a much lower heat
increment in the rumen (Van Soest, 1982) and thus it can provide
energy without a negative thermal side effect.
Glucose: Based upon some of our recent data, maximizing rumen production
of glucose precursors (i.e. propionate) could be an effective strategy to
maintain milk production. However, due to the rumen health issue,
increasing dietary grain should be performed with care. A safe and
effective method of maximizing rumen propionate production can be
through the use of monensin (approved for lactating dairy cattle in 2004).
In addition, monensin may assist in stabilizing rumen pH during stress
situations (Schelling, 1984). Proplyene glycol is typically fed in early
lactation but may also be an effective method of increasing propionate
production during heat stress. With the increasing demand for biofuels
and subsequent supply of glycerol, it will be of interest to evaluate the
efficacy and safety of glycerol in ruminant diets during the summer
months.
53
DCAD: Maintaining a negative DCAD during the dry period and a positive
DCAD during lactation is a good strategy to maintain health and maximize production (Block, 1994). It appears that keeping the DCAD at a
healthy lactating level (~+20 to +30 meq/100 g DM) remains a good
strategy during the warm summer months (Wildman et al., 2007).
Minerals: Unlike humans, cattle utilize potassium (K+) as their primary osmotic regulator of water secretion from their sweat glands. As a consequence, K+ requirements are increased (1.4 to 1.6% of DM) during
the summer and this should be adjusted for in the diet (West, 2002).
In addition, dietary levels of sodium (Na+) and magnesium (Mg+)
should be increased as they compete with K+ for intestinal absorption
(West, 2002).
SUMMARY
Clearly the heat-stressed cow implements a variety of postabsorptive changes in both carbohydrate and lipid metabolism (i.e. increased insulin action) that would not be predicted based upon their
energetic state. The primary end result of this altered metabolic condition is that the heat-stressed lactating dairy cow has an extra need for
glucose (due to its preferential oxidization by extra-mammary tissue).
Therefore, any dietary component that increases propionate production (the primary precursor to hepatic glucose production), without reducing rumen pH, may increase milk yield. In addition, reducing systemic insulin sensitivity will increase glucose availability to the mammary and thus also probably increase milk yield.
Note: This article has been adapted from papers published by the authors in
Proceedings in the 2007 Southwest Nutrition Conference and Proceedings in
the 2007 Cornell Nutrition Conference.
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Kadzere, C.T., MR. Murphy, N. Silanikove and E. Maltz. 2002. Heat stress in
lactating dairy cows: a review. Livestock Prod. Sci. 77:59-91.
Lucy, M.C., C.R. Staples, W.W. Thatcher, P.S. Erickson, R.M. Cleale, J.L.
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and improving energy balance during times of nutrient limitation. Proc.
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Moore, C.E., J.K. Kay, M.J. VanBaale, R.J. Collier and L.H. Baumgard. 2005b.
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reproduction. Proc. Tri-State Nutr. Conf. 1-9.
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56
Rethinking Nutritional Management During the Dry Period and Transition
James K. Drackley
Department of Animal Sciences
University of Illinois at Urbana-Champaign
email: drackley@uiuc.edu
Introduction
Many dairy operations large and small continue to be plagued by a high
incidence of metabolic disorders and infectious diseases around calving. Turbulent transitions increase health care expenses, decrease milk production, impair
reproductive performance, and result in premature culling or death. Farm profitability and animal well-being both suffer. Despite many years of research and
field emphasis, practical management strategies to minimize health problems
while still promoting high milk production have remained elusive.
Over the last 20 years, higher energy and nutrient density rations have
been fed during the close-up (pre-fresh) period, generally beginning around 3
weeks before expected calving. This approach was designed on the basis of
research showing advantages in adaptation of the rumen microbial population
and rumen papillae to higher nutrient diets fed after calving, decreased body fat
mobilization and fat deposition in liver, and maintenance of blood calcium concentrations. Although each of these ideas were sound and based on good research data, the ability of higher-energy close-up or “steam-up” diets to minimize production diseases in research trials and field experience has been disappointing and frustrating. Overall, data fail to demonstrate that steam-up diets
reliably and repeatedly improve production, body condition, reproduction, or
health after calving.
We have been frustrated by this lack of success in both research and
field settings and have searched for a better approach to dry cow nutritional
management. The concepts presented in this paper in many ways are nothing
new, as they center on formulating dry cow rations to dietary energy densities
that were established many years ago by the National Research Council (NRC).
Rethinking what these data and previous knowledge tell us about dry cows has
led us to a new interpretation relative to the existing dogma, and to develop a
practical system suitable for modern dairy management practices on both small
and large dairies.
Controlled Energy Intake During the Dry Period
Our research group has investigated whether controlling energy intake
during the dry period might lead to better transition success (Grum et al., 1996;
Drackley, 1999; Drackley et al., 2001, 2005; Dann et al., 2005, 2006; Douglas et
al., 2006; Loor et al., 2005, 2006). Our research drew both from our ideas and
observations as well as from field experiences by individuals such as Dr. Gordie
Jones and Dr. Peter Drehmann.
57
The data we have collected demonstrate that cows fed even moderateenergy diets (0.68 – 0.73 Mcal NEL/lb DM) will easily consume 40 – 80% more
NEL than required during both far-off and close-up periods. Cows in these studies were all less than 3.5 body condition score at dry-off, were housed in individual stalls, and were fed diets based on corn silage, alfalfa silage, and alfalfa hay
with some concentrate supplementation. We have no evidence that the extra
energy and nutrient intake was beneficial in any way. More importantly, our data
indicate that allowing cows to over-consume energy to this degree may predispose them to health problems during the transition period if they face additional
management challenges that create stress responses or limit feed intake.
We have collected a variety of data indicating that prolonged overconsumption of energy during the dry period can result in poorer transitions.
These data include whole-animal responses important to dairy producers such
as lower post-calving dry matter intakes and slower starts in milk production
(Douglas et al., 2006; Dann et al., 2006). We also have demonstrated that overfeeding results in negative responses of metabolic indicators, such as higher
nonesterified fatty acids (NEFA) in blood and more triglyceride or fat in the liver
after calving (Douglas et al., 2006; Janovick Guretzky et al., 2006). From a basic-science standpoint, there are alterations in cellular (Litherland et al., 2003)
and gene-level responses (Loor et al., 2005, 2006) that potentially explain many
of the changes at cow level.
Our data demonstrate that allowing dry cows to consume more energy
than required, even if cows do not become noticeably over-conditioned, results
in responses that would be typical of overly fat cows. Because energy that cows
consume in excess of their requirements must either be dissipated as heat or
stored, we speculate that the excess is accumulated preferentially in internal
adipose tissue (fat) depots in some cows. The NEFA and signaling molecules
released by some of these visceral adipose tissues go directly to the liver, which
may cause fatty liver, subclinical ketosis, and other secondary problems with
liver function. Humans differ in their tendencies to accumulate fat in different
locations, and central obesity is a greater risk factor for disease. Similarly, cows
might also vary in the degree to which they accumulate fat internally. In many
cases, the mechanisms we have been studying in dry cows are similar to those
from human medical research on obesity, type II diabetes, and insulin resistance.
Other research groups around the US (Holcomb et al., 2001) and in
other countries (Agenas et al., 2003; Kunz et al., 1985; Rukkwamsuk et al.,
1998) have reached similar conclusions about the desirability of controlling energy intake during the dry period. Our work has extended the ideas to show that
over-consumption of energy is common even when feeding typical dry period
diets thought to be “safe”, and that this may be a predisposing factor to poor
health. We also have extended the idea of the high-straw, low-energy ration as
a simple and practical approach to achieve the control of energy intake.
58
Our solution to the potential for cows to over-consume energy is to formulate rations of relatively low energy density (0.59 – 0.63 Mcal NEL/lb DM) that
cows can consume free choice without greatly exceeding their daily energy requirements. Note that we are not proposing to limit energy intake to less than
cows’ requirements, but rather to feed them a bulky diet that will only meet their
requirements when cows consume all they can eat. We have termed this the
“Goldilocks diet” (Drackley and Janovick Guretzky, 2007) because, like the story
of Goldilocks and the three bears, we don’t want the cow to consume too much
or too little energy, but rather just the right amount to match her requirements.
To accomplish the goal of controlled energy intake requires that some
ingredient or ingredients of lower energy density be incorporated into diets containing higher-energy ingredients such as corn silage, good quality grass or legume silage, or high quality hay. Cereal straws, particularly wheat straw, are
well-suited to dilute the energy density of these higher-energy feeds, especially
when corn silage is the predominant forage source available. Lower quality
grass hays also may work if processed appropriately, but still may have considerably greater energy value than straw and thus are not as effective in decreasing energy density.
We are aware of no controlled data comparing different types of straw,
but it is the general consensus among those who have years of experience using straw that wheat is preferred. Barley straw is a second choice, followed by
oat straw. While reasons for these preferences are not entirely clear, wheat
straw is more plentiful, is generally fairly uniform in quality, and has a coarse,
brittle, and hollow stem that process easily, is palatable, and seems to promote
desirable rumen fermentation conditions. Barley straw lacks some of these
characteristics. Oat straw is softer and as a result does not process as uniformly. In addition, oat straw generally is somewhat more digestible and thus
has greater energy content.
It is critical that the straw or other roughage actually be consumed in the
amounts desired. If cows sort out the straw or other high bulk ingredient, then
they will consume too much energy from the other ingredients and the results
may be poor. A TMR is by far the best choice for implementing high-straw diets
to control energy intake. Some TMR mixers can incorporate straw without prechopping and without overly processing other ingredients, but many mixers cannot. Straw may need to be pre-chopped to 2-in or less lengths to avoid sorting
by the cows.
59
Advantages and Beneficial Outcomes
Based on our research and field observations, adoption of the highstraw, low-energy TMR concept for dry cows might lead to the following benefits:
·
Successful implementation of this program essentially eliminates occurrence of displaced abomasum. This may result from the greater rumen
fill, which is maintained for some period of time even if cows go off feed
for some reason, or from the stabilizing effect on feed intake (Janovick
Guretzky et al., 2006).
·
Field survey data collected by the Keenan company in Europe (courtesy
of D. E. Beever, Richard Keenan and Co., Borris, Ireland) show strong
indications of positive effects on health. In 277 herds (over 27,000 cows)
in the United Kingdom, Ireland, France, and Sweden, changing to the
high-straw low-energy TMR system decreased assisted calvings by
53%. In addition, the change decreased milk fevers by 76%, retained
placentas by 57%, displaced abomasum 85%, and ketosis by 75%. Using standard values for cost of these problems, the average increase in
margin per cow in these herds was $114 just from improved health
alone. While these are certainly not controlled research data, they are
consistent with the results in our research as well as field observations in
the USA.
• The same sources of observational data indicate that body condition, re
productive success, and foot health may be improved in herds struggling
with these areas.
·
Although data are limited, milk production appears to be similar to or
slightly lower than results obtained with higher-energy close-up programs. There is some evidence that persistency may be improved, with
cows reaching slightly lower and later peak milk. Therefore, producers
should be careful to not evaluate the system based on early peaks and
should look at total lactation milk yield, daily milk, and, over time, indices
of reproduction and other non-milk indicators of economic value.
• Straw and corn silage generally are lower in potassium and thus help control the dietary cation-anion difference (DCAD) without excessive addition of anionic salt mixtures.
• The program may simplify dry cow management and ration composition in
many cases.
• Depending on straw cost, the ration likely will be no more expensive than
the average cost of far-off and close-up diets, and could be cheaper
where straw is plentiful.
60
Single Diet Dry Cow Management?
Our most recent research (Janovick Guretzky et al., 2006) as well as
considerable field experience indicates that a single-diet dry cow program can
be successful using these principles. matter intakes remain more constant as
cows approach calving when fed the high-straw low energy diets (Dann et al.,
2006; Janovick Guretzky et al., 2006) than in cows fed high-energy close-up
diets (Grummer et al., 2004). Single-group systems would have the advantage
of eliminating one group change, which may decrease social stressors as described by University of Wisconsin researchers (Cook, 2007). Single-group
management may work particularly well for producers managing for shorter dry
periods.
A variation is to maintain far-off and close-up diets, with essentially the
same diet for except that a different concentrate mix or premix is used for the
close-ups, which may incorporate anionic salts, extra vitamins and minerals,
additional protein, or selected feed additives. The optimal high-forage lowenergy dry cow ration will contain the primary forages grains to be fed in the lactation diet, but diluted with straw or low-quality forage to achieve desired energy
density. In this way, the rumen still can be adapted to the types of ingredients
be fed after calving without excessive energy intake during the dry period.
If producers desire to maintain the conventional two-group or “steam-up”
philosophy for cow feeding, our research has shown that the most critical factor
is to ensure that the energy density of the far-off dry period diet is decreased to
near NRC (2001) recommendations (NEL of − 0.60 Mcal/lb DM) so that cows do
not over-consume energy (Dann et al., 2006). In this research, wide extremes in
close-up nutrient intake had very little effect compared with the effect allowing
cows to consume excess energy during the far-off period.
Specifications for Dry Period Diets
The controlled energy system works best for producers who are relying
on corn silage as primary forage. The combination of straw and corn silage is
complementary for many reasons, including energy content, low potassium contents, starch content, and feeding characteristics.
The NEL requirement for 1500-lb Holstein cows is between 14 and 15
Mcal per day NRC, 2001). Some suggested guidelines for formulation of controlled energy diets to meet that requirement are as follows, on a total ration DM
basis.
·
Dry matter intake: 25 to 27 lb per day. For far-off cows, intakes by individual cows have often exceeded 30 lb DM per day.
•
Energy density: 0.59 – 0.63 Mcal NEL/lb DM (discussed in more detail in
a later section).
61
• Protein content: 12 to 14% of DM as CP; >1,000 g/day of metabolizable
protein as predicted by the NRC (2001) model or CNCPS/CPM Dairy
model.
• Starch content: 12 to 16% of DM.
• Forage NDF: 40 to 50% of total DM, or 10 to 12 lb daily (0.7 to 0.8% of
body weight). Target the high end of the range if more higher-energy
fiber sources (like grass hay or low-quality alfalfa) are used, and the low
end of the range if straw is used.
• Total ration DM content: <55% (add water if necessary). Additional water
will help hold the ration together and improve palatability.
·
Follow standard guidelines for mineral and vitamin supplementation. For
close-ups, target values are 0.40% magnesium (minimum), 0.35 –
0.40% sulfur, potassium as low as possible, a DCAD of near zero or
negative, 0.27% phosphorus, and at least 1,500 IU of vitamin E. Recent
data suggests that calcium does not have to be increased beyond 0.6%
of DM (Lean et al., 2006).
An example formulation is included in Table 1, from a recently completed experiment by our group (Janovick Guretzky et al., 2006). The example
is for the far-off dry cow group, but the close-up diet was essentially identical
except for the addition of anionic salts.
As long as the lactation diet is formulated appropriately, there seems to
be little difficulty in transitioning to the lactation diet immediately after calving.
Many producers have found that inclusion of ½ to 2 lb of chopped straw in the
lactation diet improves rumen function and animal performance, particularly
when physical fiber is borderline adequate. Addition of the straw postpartum
also may help to ease the transition from the lower-energy dry cow diet.
Deciphering NEL Values
The NEL value specified for the same diet may vary considerably depending on method used to derive the value. While we have used NEL widely to
formulate and evaluate high-straw low-energy diets, nutritionists, veterinarians,
and producers have expressed confusion on how to arrive at the “correct” NEL
content of the rations. Because of the confusion, it may be better to focus on
providing the recommended intakes of forage NDF (10 - 12 lb/day) as a primary
guideline for achieving the correct energy density. Nevertheless, NEL values are
important and useful if applied and interpreted carefully.
In calculating NEL values, some confusion has resulted from the changeover to the NRC (2001) equations and calculation methods, and some is related
to differences in how feed analysis laboratories calculate and report NEL values.
Those working to formulate and monitor the rations must use consistent units
for evaluating dietary NEL density to avoid confusion. Moreover, users should
realize that it is difficult to compare NEL values across locations and laboratories, so a consistent system within a farm or nutrition practice is more important.
62
An example of the potential confusion in using NEL values for high-straw
low-energy rations is shown in Table 1. The diet was fed to one group of cows
and heifers in our most recently completed experiment (Janovick Guretzky et
al., 2006). Feed ingredients were sampled weekly, formed into monthly composites, and analyzed by Dairy One Laboratory (Ithaca, NY) using wet chemistry
techniques. Using the actual measured cow variables and analyzed feed composition, we compared the NEL density of the ration calculated four different
ways. The value for the total diet calculated by the NRC (2001) model was 0.62
Mcal/lb DM. By using the analytical values for monthly composites of feed ingredients in the Cornell Net Carbohydrate and Protein System (version 5.0), the
comparable NEL value was 0.59 Mcal/lb. If we used the NEL values from Dairy
One for individual ingredients to additively calculate the total dietary NEL density, the value was 0.55 Mcal/lb DM. However, if we used the values for individual ingredients provided by Dairy One as “NRC values” for dry cows, the total
diet NEL was 0.67 Mcal/lb DM! Why the large discrepancy? Which is “correct”?
The NEL value is technically correct only for the feed that a cow actually
eats (NRC, 2001) because ingredients in a diet influence rumen digestibility of
other ingredients, some positively and some negatively. A classic example is
that concentrates added to a diet decrease digestibility of the NDF components
in forages by changing the rumen environment. Consequently, the NEL density
of a diet cannot be determined accurately by adding together the calculated NEL
values of individual ingredients. The NEL value of an individual feed ingredient is
only correct if it is fed as the only feed ingredient to a cow, which of course is
uncommon.
In addition, the digestibility of the dietary DM decreases as total feed intake increases. This decrease is more pronounced for the NDF fraction than for
starch, and is greater for grass-type forages than legumes. The NRC incorporates a standard reduction of 4 percentage units digestibility for each multiple of
maintenance intake. Because different components of the diet are affected differently by the intake effect, Van Soest (Cornell University) devised a variable
discount system. These discounts are used by Dairy One, for example, to report
an NEL value at 3× maintenance, which would be equivalent to the intake
needed to produce about 66 lb of milk (see www.dairyone.com/Forage/
FactSheet/NRC_201_Energy_Values.htm. and www.dairyone.com/Forage/
Newsletters/199903.pdf). Because the NEL value of straw is severely penalized
by the Van Soest variable discount system, the calculated value of the diet is
considerably lower than the NRC-model value for the total ration (Table 1). On
the other hand, using the laboratory values assigned to individual ingredients by
the laboratory using NRC principles and then reconstructing an “average” value
of the ration overestimates the NEL density relative to the value determined for
the total diet as consumed using the NRC (2001) model.
63
An alternate approach is to use net energy for maintenance (NEM) values instead of NEL. The NEM of a ration should, by definition, be equal to NEL at
maintenance intakes (NRC, 2001). When we used NEM provided by Dairy One
for individual ingredients to calculate energy values for the diet shown in Table
1, the total ration NEM (0.60 Mcal/lb DM) was close to the NEL value calculated
for the total diet (0.62) by the NRC (2001) model.
The bottom line is that those formulating and monitoring diets must be
consistent in which energy and laboratory units are being applied, and realize
that comparison of dietary energy values across studies, laboratories, or farms
must be done carefully and with understanding of how the values were derived.
Using the assigned NEL values from analytical laboratories may not be appropriate for dry cows fed mixed diets. Values for NEL of the total diet calculated by
using the NRC (2001) or CNCPS/CPM models will always be more accurate
predictors. Use of NEM values for individual ingredients to calculate an NEM
value for the total diet may be the most accurate unit for reconstructing a total
diet value from individual analyses.
Practices Important for Success
Three factors are critical to successfully implement this approach: 1) prevention of sorting, 2) ensuring continuous and non-crowded access to the TMR,
and 3) careful monitoring of DM content and attention to detail. Where “trainwrecks” have been reported, one or more of these factors has been faulty, not
the dietary approach itself.
The straw must be chopped into a particle size that cows will not sort out
of the ration. In general, this means less than 2” particles. If the straw is prechopped, an appropriate chop is indicated by having about 1/3 of the particles in
each of the three fractions of the Penn State shaker box. Because of the bulky
nature of straw and the resulting TMR, producers may think that cows are sorting excessively when they are not. To verify that cows are not sorting, the feed
refusals should be monitored carefully and compared to the original TMR. One
simple way to evaluate sorting is to shake out the TMR with the Penn State box
and then repeat the analysis on the feed refusals the next day. Results should
not differ by more than 10% from TMR to refusal. Another way to monitor sorting is to collect samples of the feed refusal from several areas of the feedline
and have it analyzed for the same chemical components as the TMR fed. Again,
composition of NDF, CP, and minerals should not vary by more than 10% between ration and refusal if cows are not sorting. If cows sort the straw, some
cows will be consuming a higher energy diet than formulated, and some (the
more timid cows) will be left with a much lower quality ration than desired. Herds
in which sorting is a problem will be characterized by pens of dry cows that
range widely in body condition: some will be over-conditioned and some underconditioned, while of course some may be “just right”.
Another common pitfall is poor feedbunk management that limits the
ability of cows to consume feed ad libitum. Because of the bulky nature of the
diet, cows may have to spend more time eating to consume enough feed to
meet energy and nutrient requirements. Bunk space must be adequate and feed
pushed up frequently. If feed is not pushed up, cows likely will not be able to
consume what they need to meet requirements.
64
Other common problems arise when the DM content of straw, hay, and
silages changes markedly from assumed values. This may happen, for example, if the straw is rained on or the DM content of silage changes without the
feeders knowing it. Changes in DM of the ingredients mean changes in the DM
proportions of the total diet unless the mix is corrected. Thus, energy intake may
increase or decrease relative to the target, and producers may experience a
rash of calving-related health problems until the situation is corrected.
While the nutritional concepts of these rations are simple, the approach
and implementation are not problem-free. Attention to detail is a must. The system is not an “easy” or a lazy approach to dry cow care. When implemented
correctly, results have been exceptional. However, high-straw low-energy diets
are not remedies for poor feeding management or bad facilities. Applied in
these situations, results may be poor.
Additional Considerations
As mentioned earlier, the combination of straw and corn silage, along
with other lactation ration ingredients, works well because of the complementary
features of the components in the total diet. Straw has many desirable characteristics that seem to improve health and digestive dynamics in the rumen. The
slow digestion and passage rate of straw certainly seems to be important in prevention of DA. We feel that the control of energy intake is a critically important
factor in maintaining a more constant energy intake during the dry period and in
preventing other disorders around calving such as ketosis and fatty liver.
Whether other low-energy ingredients will produce the same desirable
results remains uncertain. We are not aware of research that has compared
other low-energy ingredients such as poor-quality hay, oat hulls, cottonseed
hulls, corn stalks, soybean residue, or flax shives to straw or to conventional
rations, although we have anecdotal reports from producers and nutritionists
with varying reports of success. With roughage-type materials, the key consideration is uniform processing and palatability so that cows do not sort and the
formulated profile of nutrients is actually consumed. For concentrate-type or
finely ground ingredients, energy content is low but particle size is so small that
rate of passage can be too fast, allowing particles to escape more quickly even
though they are not digested. In this case, DMI by the cows may increase so
that total energy intake still exceeds requirements considerably.
Good-quality straw is a consistent (but low) source of nutrients, although
its composition still can be variable (NRC, 2001). Table 2 shows means, standard deviations, and ranges for straw samples over two years during two recent
experiments from our group (Dann et al., 2006; Janovick Guretzky et al., 2006).
The mean values are close to those reported in NRC (2001), although CP was
lower and NDF higher in our samples. Also of note, analyzed concentrations of
potassium and sodium were considerably lower than means reported by NRC
(2001).
Just because straw or other low-energy ingredients are “low quality” by
conventional standards of evaluation based on protein or energy content does
not mean that other measures of “quality” can be ignored. Straw or other feeds
that are moldy, severely weather-damaged, or have fermented poorly should
not be fed to dry cows, especially the close-ups.
65
Comparisons of high-straw low-energy diets with conventional diets in
cows of widely differing body condition scores are not available. In the field, the
diets seem to work well in both thin and fat cows. In fact, many producers have
concluded that these diets are the best way to manage obese cows through
calving to minimize the usual problems expected with fat cows.
Conclusions
High-straw low-energy rations are exciting for their potential to markedly
improve health during the transition period. The key concept is to strive to meet
the requirements of cows for energy and all other nutrients, but to not allow
cows to exceed their requirements for energy by large amounts for the duration
of the dry period. Provided that these high-straw low-energy rations are formulated, mixed, and delivered properly, results have been positive. Research and
field observations indicate that the rations result in better energy balance after
calving, with subsequent improvements in health. Milk production is maintained,
and field observations suggest that reproductive success may be improved also,
although data are lacking. Research is needed to explore other low-energy
bulky ingredients as options to straw.
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Litherland, J. P. Underwood, and J. J. Loor. 2005. Physiological and
pathological adaptations in dairy cows that may increase susceptibility to
periparturient diseases and disorders. Ital. J. Anim. Sci. 4:323-344.
66
Drackley, J. K., and N. A. Janovick Guretzky. 2007. Controlled energy diets for
dry cows. Pages 7-16 in Proc. 8th Western Dairy Mgt. Conf., Reno, NV.
Oregon St. Univ., Corvallis.
Drackley, J. K., T. R. Overton, and G. N. Douglas. 2001. Adaptations of glucose
and long-chain fatty acid metabolism in liver of dairy cows during the periparturient period. J. Dairy Sci. 84(E. Suppl.):E100-E112.
Grum, D. E., J. K. Drackley, R. S. Younker, D. W. LaCount, and J. J. Veenhuizen. 1996. Nutrition during the dry period and hepatic lipid metabolism
of periparturient dairy cows. J. Dairy Sci. 79:1850-1864.
Grummer, R.R., D.G. Mashek, and A. Hayirli. 2004. Dry matter intake and energy balance in the transition period. Vet. Clin. Food Anim. 20:447-470.
Holcomb, C. S., H. H. Van Horn, H. H. Head, M. B. Hall, and C. J. Wilcox. 2001.
Effects of prepartum dry matter intake and forage percentage on postpartum performance of lactating dairy cows. J. Dairy Sci. 84:2051-2058.
Janovick Guretzky, N. A., N. B. Litherland, K. M. Moyes, and J. K. Drackley.
2006. Prepartum energy intake effects on health and lactational performance in primiparous and multiparous Holstein cows. J. Dairy Sci. 89
(Suppl. 1). (Abstr.)
Kunz, P. L., J. W. Blum, I. C. Hart, J. Bickel, and J. Landis. 1985. Effects of different energy intakes before and after calving on food intake, performance
and blood hormones and metabolites in dairy cows. Anim. Prod. 40:219231.
Lean, I. J., P. J. DeGaris, D. M. McNeil, and E. Block. 2006. Hypocalcemia in
dairy cows: meta-analysis and dietary cation anion difference theory revisited. J. Dairy Sci. 89:669-684.
Litherland, N. B., H. M. Dann, A. S. Hansen, and J. K. Drackley. 2003. Prepartum nutrient intake alters metabolism by liver slices from peripartal dairy
cows. J. Dairy Sci. 86(Suppl. 1):105-106. (Abstr.)
Loor, J. J., H. M. Dann, R. E. Everts, R. Oliveira, C. A. Green, N. A. JanovickGuretzky, S. L. Rodriguez-Zas, H. A. Lewin, and J. K. Drackley. 2005.
Temporal gene expression profiling of liver from periparturient dairy cows
reveals complex adaptive mechanisms in hepatic function. Physiol. Genomics 23:217-226.
67
Loor, J. J., H. M. Dann, N. A. Janovick Guretzky, R. E. Everts, R. Oliveira, C. A.
Green, N. B. Litherland, S. L. Rodriguez-Zas, H. A. Lewin, and J. K.
Drackley. 2006. Plane of nutrition pre-partum alters hepatic gene expression and function in dairy cows as assessed by longitudinal transcript and
metabolic profiling. Physiol. Genomics 27:29-41.
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Rukkwamsuk, T., T. Wensing, T., and M. J. Geelen. 1998. Effect of overfeeding
during the dry period on regulation of adipose tissue metabolism in dairy
cows during the periparturient period. J. Dairy Sci. 81:2904-2911.
www.dairyone.com/Forage/FactSheet/NRC_201_Energy_Values.htm.
cessed 12/1/06.
www.dairyone.com/Forage/Newsletters/199903.pdf. Accessed 12/1/06.
68
Ac-
Table 1. Example high-straw, low-energy diet fed during the far-off dry period
(Janovick Guretzky et al., 2006)
Amount in ration
(DM basis)
Item
Ingredients
Corn silage, %
35.3
Chopped wheat straw, %
31.8
Chopped alfalfa hay, %
17.1
Corn grain, ground, dry, %
3.6
Soybean meal, solvent, 48% CP, %
5.1
SoyPlus, %
4.0
Urea, %
0.9
Minerals and vitamins, %
2.2
Composition
Forage NDF, %
50.4
NFC, %
25.4
CP, %
14.4
NRC Metabolizable protein, g/d at 26.5 lb DMI
1,085
a
0.62
b
0.59
c
0.55
d
0.67
e
0.60
NEL, Mcal/lb DM
NEL, Mcal/lb DM
NEL, Mcal/lb DM
NEL, Mcal/lb DM
NEM, Mcal/lb DM
a
Calculated for the total diet using the NRC (2001) model and analyzed
chemical composition for corn silage, wheat straw, alfalfa hay, and concentrate mixture.
b
Calculated for the total diet using the CNCPS (version 5.0) model and analyzed chemical composition for corn silage, wheat straw, alfalfa hay, and concentrate mixture.
c
Calculated additively using NEL values assigned by Dairy One Laboratory for
individual ingredients, using the Van Soest variable discount factors and correct at intake of 3× maintenance.
d
Calculated additively using NEL values provided by Dairy One Laboratory
using NRC 2001 equations (Ohio State summative equation) for individual ingredients, at intake appropriate for dry cows.
e
Calculated using NEM values for individual ingredients as specified by Dairy
One Laboratory.
69
Table 2. Chemical composition of wheat straw in University of Illinois experiments.1
Component
DM, % as fed
CP, % of DM
Soluble protein, % of CP
NDF, % of
DM
ADF, % of DM
NFC, % of
DM
TDN, %
NEM, Mcal/lb
DM
Ca, % of DM
P, % of DM
Mg, % of DM
K, % of DM
S, % of DM
Na, % of DM
Fe, ppm of
DM
Zn, ppm of
DM
Cu, ppm of
DM
Mn, ppm of
DM
Mean
93.3
3.8
44.2
Standard Deviation
0.82
0.83
9.6
Maximum
94.5
5.3
65.0
Minimum
91.2
2.4
25.0
79.6
3.7
85.2
69.9
53.3
11.6
2.9
3.0
59.0
19.2
45.8
6.8
49
0.35
1.4
0.06
53
0.43
47
0.12
0.27
0.08
0.12
1.30
0.07
0.02
117
0.11
0.03
0.04
0.12
0.03
0.01
68
0.57
0.14
0.26
1.53
0.18
0.06
303
0.08
0.05
0.09
0.95
0.04
0.01
53
16
11.6
59
7
8
4.1
18
4
75
15.3
119
51
1
Values are from 21 monthly composite samples from two experiments (Dann
et al., 2006; Janovick Guretzky et al., 2006) analyzed by wet chemistry techniques at the same laboratory (Dairy One, Ithaca, NY).
70
Observations on Seasonal Pasture-Based Dairy Production
Steven P. Washburn
Department of Animal Science
North Carolina State University
Phone: 919-515-7726
Steve_Washburn@ncsu.edu
Objective: The intent of this paper is to examine concepts and challenges associated with seasonal breeding and calving in pasture-based dairy production
systems. Although emphasis is primarily on pasture-based dairy production systems, some principles may be applicable to other dairy production systems.
Why consider seasonal breeding and calving? Potentially advantages for
using seasonal breeding and calving in a dairy management system include
matching forage availability to nutrient needs, lower feeding costs, having fewer
different groups of animals at any one time, being able to concentrate on specific tasks within short periods, and to vary the farm workload across the year.
Less manure storage is needed and cows do a good job of recycling manure
nutrients if pastures are managed intensively (White et al., 2001). In pasturebased systems, cows rarely need hoof trimming, are unlikely to have displaced
abomasums, and typically have fewer cases of clinical mastitis. However, there
may be increased risk for milk fever and grass tetany.
Capital investment for equipment and housing in pasture-based seasonal dairy
herds is expected to be lower than more conventional systems (White et al.
2002). However, investment in land and milking facilities can be substantial.
Sufficient pasture land must be available within walking distance (~1 mile) of
milking facilities. Typically, pasture-based seasonal herds are managed with
milking facilities that allow for the entire herd to be milked in under 2.5 hours for
each milking. Swing milking systems are often used because of the efficient
throughput of cows. Such systems may have only 8 or 10 units in smaller herds
but may have as many as 45 units for herds up to about 700 cows. For larger
pasture-based herds, rotary milking parlors with 60 or more milking units are
more common.
With all of the calves being born within a few weeks, rearing of calves is usually
in group-feeding competitive situations. Milk feeding can be either once a day to
reduce labor or twice a day if preferred. At our fall-calving pasture-based research herd in Goldsboro, NC, we usually teach calves to drink a gallon of milk
from a bucket and them put them in groups of 10 to 20 calves and feed them
milk once a day in a trough on pasture with access to a calf starter. Farms may
provide groups of calves access to nipples on barrels or to portable milk feeders
with up to 60 nipples.
71
Disadvantages to pasture-based seasonal breeding and calving. Usually, a
pasture-based seasonal herd does not produce as much milk per cow as a
TMR-fed confinement herd so the gross income per cow is expected to be
lower. Matching the forage availability to the calving season may not result in
the highest average milk prices and farm net income may not be enhanced
even with lower feeding costs. Management of cash flow can be an issue with
variable levels of milk income across the year. Inconsistent rainfall patterns result in variable amounts of available pasture. Therefore, irrigation or other
drought-management strategies need to be considered.
In seasonal herds, there is much more work from the start of calving through
rebreeding which could add to farm family stress levels. Some dairy producers
may prefer to have a more consistent workload for themselves and their employees. There is risk involved with needing to breed all the cows in a short period of time. Low conception rates, untimely disease outbreaks, or a nutritional
crisis could lead to failure to get cows bred within a reasonable period, thereby
disrupting a seasonal calving strategy.
Matching calving season to forage availability. In countries where seasonal
breeding and calving in dairy cattle is most common, matching the feed resources to the nutrient needs of the animal is of primary importance. For example, in New Zealand and Ireland perennial ryegrass (Lolium perenne L.) is the
primary forage species. Therefore, late winter or early spring calving is usually
implemented so that cows have access to abundant high quality pasture as they
reach peak milk production and approach the time of rebreeding. With renewed
interest in pasture-based dairy systems in recent years in the U.S., many producers in areas where cool-season forages are abundant have similarly
adopted a late winter-early spring calving pattern with the breeding season usually starting in May and ending some time in July or early August. However,
breeding during June through September poses a physiological problem in
warmer areas including subtropical regions. Higher ambient temperatures often
accompanied with high humidity result in very low conception rates, thereby reducing the proportion of cows that successfully breed within the desired period.
In such areas, compact calving seasons usually are planned within a range of
dates from the middle of August until late early March so that breeding can be
done during cooler times of the year. This usually means that a combination of
warm season and cool season annual and perennial forages may be needed.
A particular season of calving may be based on personal preference. One Vermont dairy producer likes for his cows to be dry in late summer so that he can
go fishing. He indicated a need to feed cows in the winter anyway so milking in
fall, winter, and spring and to take his break in summer suited him better. Certainly, if a high percentage of farms chose to be seasonal in the same season,
price incentives would likely occur for calving at other times of the year. In New
Zealand, most of the milk is seasonally produced, then processed and exported.
Therefore, incentives are paid so that some producers will supply fluid milk for
local use through the winter months. However, even in those circumstances,
dairy producers often choose to manage the herds in relatively compact calving
groups, often having two distinct calving seasons rather than calving year
round. This allows for efficient management of animals within similar physiological or age groups.
72
Theoretical expectations for seasonal breeding success. For a very compact calving period of 6 weeks, cows would typically range from 40 to 85 days at
the start of breeding and most would be expected to be cyclic at that time. If
90% of cows were cyclic and submitted for breeding with 60% conception, then
54% of the herd would be expected to conceive in the first 21 days of the breeding season. At the end of 6 to 9 weeks of breeding, approximately 79% to 90%
of the herd would be pregnant. Conception rates of 48% or 36% would be less
efficient and result in only 68% or 54%, respectively of cows conceiving in 42
days. Cumulative pregnancy rates at lower conception would not be acceptable
unless the breeding season was extended to 12 or 14 weeks (Table 1). If a calving season was 9 weeks, the late calvers would be only about 3 weeks postpartum and some cows likely would not be cyclic at the start of breeding. At 80%
submission and 60% conception, 48% of cows would conceive in the first 21
days and 9 weeks of breeding would achieve a pregnancy rate of 86%. At 80%
submission rate with conception rates of 48% or 36%, longer breeding periods
would be needed to ensure adequate overall pregnancy. A 12-week calving
season means that rebreeding would begin just as the last cows were calving.
The 21-day submission rate would be lower (e.g. 70%) and breeding periods
would need to be extended with decreasing conception rates in order to achieve
comparable pregnancy rates to herds with more compact calving patterns. Herd
conception rates below 40% are not likely to result in acceptable pregnancy
rates for seasonal breeding (Table 1).
Observed results for seasonal breeding success in dairy cattle. In New
Zealand, 897 cows of which 14% were Jersey and 86% were Holstein-Friesian
were evaluated for fertility in 2,594 lactations from 1986 to 2000 (Roche et al.,
2007). After only 3 weeks of breeding, 50 to 65% of cows were pregnant with
higher proportions pregnant related to less body condition loss postpartum and
to more weight gain during the breeding season. Breeding for 6 weeks resulted
in 69 to 85% pregnant whereas 12 weeks of breeding resulted in 87 to 97%
pregnancy. The high success rate by 21 days and beyond is consistent with a
very high percentage of cyclic cows and very high conception rates. In Ireland,
Buckley et al. (2000) compared Holstein-Friesians (52% modern Holstein) of
moderate genetic merit to Holstein-Friesians (92% modern Holstein) of high genetic merit in a seasonally breeding pasture-based study. In 2 years of data,
94% of moderate genetic merit cows became pregnant whereas only 80% of the
higher genetic merit cows conceived after 13 weeks of breeding. Although 3.7
kg/day (8.1 lbs) more milk was produced by the higher genetic merit cows, the
authors concluded that the increased milk yield would not fully compensate for
the increased culling that would result from lower cow fertility.
73
In our own seasonal breeding work in North Carolina, conception rates were
higher in Jerseys (60%) than Holsteins (50%) and pregnancy rates after 75
days (~11 weeks) of breeding were 78% and 58%, respectively (Washburn et
al., 2002b). Part of the difference was that only 86% of Holstein cows were detected in estrus whereas 96% of Jerseys were detected in estrus. No effect of
season of breeding (fall vs. spring) was observed and although not significant
pasture-fed cattle had numerically higher pregnancy rates than cattle fed a total
mixed ration. More recently, fertility in a fall-calving pasture-based herd of cows
with Jerseys, Holsteins, and crossbred cows has been summarized (CM Williams, 2007 MS Thesis – NC State Univ., in press). Across the 2005 and 2006
breeding seasons, 90 days (about 13 weeks) of AI breeding resulted in 90% of
Jersey cows, 86% of crossbred cows, but only 70% of Holstein cows being confirmed pregnant. Fewer Holsteins were cyclic early after calving and Holsteins
also had lower first service conception rates in both years.
In personal communication with several seasonal dairy graziers in the US, success rates are variable with a combination of AI and natural service breeding.
Reaching 80 to 90% pregnant after 8 to 12 weeks of breeding is often achieved
but is not guaranteed. In many cases, such herds have mostly crossbred cows
and/or a significant influence of Jersey or New Zealand Friesian genetics.
In 11 seasonal herds in NZ, use of a combination of progesterone, estradiol,
and prostaglandin for estrous synchronization at the beginning of the breeding
season was examined (Xu et al., 1996). The percentage of cows inseminated in
the first 5 days was 89.0% for the synchronized group compared to 29.7% for
the control group. However, conception rates were lower at both first and second insemination such that the percentages of cows pregnant after several
weeks of AI were not different (81.8% vs. 85.5% for controls) and the mean day
of pregnancy was advanced only 1.3 days by synchronization. Because of potentially adverse effects on conception among cyclic cows, it is more common to
use hormonal intervention only on cows that are not cyclic at the planned start
of breeding (Rhodes et al., 2003). In some herds, cows that are bred late may
be induced to calve a few weeks early in order to get the lactation initiated. This
practice is now discouraged in New Zealand and is being replaced by selecting
bulls for shorter gestation length for breeding late in the season.
Should a selection index differ for seasonal breeding dairy herds? Although fertility in dairy cattle has low estimates for heritability, there is substantial evidence that genetic aspects are important. In 2003, the USDA’s Animal
Improvement Programs Laboratory (AIPL), began to include daughter pregnancy rate (DPR) at 7% of the weighting in the evaluation of dairy sires for Net
Merit$ in the USDA sire summaries (http://aipl.arsusda.gov/reference/
nmcalc.htm). With adjustment in the Net Merit$ calculations in 2006 to include
even more emphasis on fitness traits, the weighting on DPR was increased to
9%. Because of the critical importance of fertility for seasonal breeding herds,
the possibility of placing even more emphasis on DPR is of interest (Norman et
al., 2006).
74
Results from ranking of the top 10% of active US Holstein bulls for current Net
Merit$ in comparison to increasing emphasis on DPR by 2X (18%) or 3X (27%)
is shown in Table 2 along with a ranking based on using DPR alone. In order to
allow more emphasis on fertility, adjustments in the weighting of other traits is
necessary. This was done by reducing the relative weighting on fat and protein
with slight decreases in emphasis on somatic cell scores (SCS) and the udder
composite. Also, because of the efficiency preference for a smaller cow in grazing systems, more negative weighting was placed on cow body size. When the
top 10% of 656 Holstein bulls were averaged for current Net Merit$, milk was at
+1,254 pounds (570 kg), DPR was at +0.4% and productive life was +3.0
months. Doubling the weighting on DPR, resulted in the top 66 bulls averaging
4.5% lower milk, 17% lower fat, 4.8% lower protein but they had higher DPR
(+0.9%) and productive life (3.5 months). Therefore the Net Merit$ value for
those bulls was only 5% lower than top bulls based on current Net Merit$. Tripling the emphasis on DPR, did reduce milk by 18.5%, fat by 30%, and protein
by 16.7% but increases in DPR to +1.3% and PL to +3.8 months resulted in only
a net reduction of only 6% in Net Merit$. In contrast, just ranking bulls only on
DPR, provided the highest DPR at +1.8% as expected but milk, fat, protein, and
Net Merit$ were all substantially lower by 48.9%, 63.3%, 42.9%, and 26.9%,
respectively (Table 2).
Therefore, it seems reasonable that dairy producers with interests in seasonal
breeding and calving may want to use a selection index that places more
weighting on fertility. Even for herds not planning to be seasonal, using sire
summaries to avoid using bulls that are very negative for daughter pregnancy
rates could be useful in helping to reverse the long negative trend in dairy cow
fertility (Washburn et al., 2002a). However, selecting bulls for AI use based only
on DPR is not justified because of substantial reduction in other traits of economic importance.
Conclusions: Seasonal breeding and calving as part of a pasture-based dairy
system is an attractive option for some dairy producers for reasons of lifestyle
as well as for matching nutritional requirements to forage quality and availability
in pasture-based systems. However, having herd fertility high enough to consistently maintain seasonality can be a challenge. Breed differences in fertility are
evident but improved fertility within breed can likely be achieved by placing
more emphasis on daughter pregnancy rates in selecting sires to use. As with
any dairy production system, differing strategies will likely be optimal for producers with differing resources and goals. Although milk production per cow is usually less, advantages in lower facility and equipment costs, lower feed costs,
and improved animal health provide the opportunity for well-managed seasonal
pasture-based dairy systems to be economically competitive.
75
References:
Buckley, F., P. Dillon, M. Rath, and R.F. Veerkamp. 2000. The relationship between genetic merit for yield and live weight, condition score, and energy
balance of spring calving Holstein Friesian dairy cows on grass based
systems of milk production. J Dairy Sci 83: 1878-1886.
Norman, H. D., J. R. Wright, and R. L. Powell. 2006. Is there a need for different
genetics in dairy grazing systems? In: Proceedings of the 6th Mid-Atlantic
Dairy Grazing Conference: October 31- November 1, 2006. Center for
Environmental Systems, Goldsboro, NC.
http://www.cefs.ncsu.edu/PDFs/Dairy%20Conferece%20Proceedings/Dairy%
20Proceedings%20Home.html
Rhodes, F. M., S. McDougall, C. R. Burke, G. A.Verkerk, and K. L. Macmillan.
2003. Invited Review: Treatment of cows with an extended postpartum
anestrous interval. J Dairy Sci 86: 1876-1894.
Roche, J. R., K. A. Macdonald, C. R. Burke, J. M. Lee, and D. P. Berry. 2007.
Associations among body condition score, body weight, and reproduce
tive performance in seasonal-calving dairy cattle. J Dairy Sci: 90: 376391.
Washburn, S.P., W.J. Silvia, C.H. Brown, B.T. McDaniel, and A.J. McAllister.
2002a. Trends in reproductive performance in Southeastern Holstein
and Jersey DHI herds. J. Dairy Sci. 85: 244-251.
Washburn, S.P., S.L. White, J.T. Green, Jr., and G.A. Benson. 2002b. Repro
duction, mastitis, and body condition of seasonally calved Holstein and
Jersey cows in confinement or pasture systems. J. Dairy Sci. 85: 105111.
White, S.L., G.A. Benson, S.P. Washburn, and J.T. Green, Jr. 2002. Milk pro
duction and economic measures in confinement or pasture systems us
ing seasonally calved Holstein and Jersey cows. J. Dairy Sci. 85: 95104.
White, S.L., R.E. Sheffield, S.P. Washburn, L.D. King, and J.T. Green, Jr. 2001.
Spatial and time distribution of dairy cattle excreta in an intensive pas
ture system. J. Environ. Qual. 30: 2180-2187.
Xu, Z. Z., L. J. Burton, and K. L. Macmillan. 1996. Reproductive performance of
lactating dairy cows following oestrus synchronisation with progesterone,
Oestradiol and prostaglandin. NZ Vet J.: 44(3):99-104
76
Table 1: Cumulative pregnancy rates1 at varied rates of submission, conception,
and length of breeding.
Submission
Rate2
Conception
Rate3
Pregnant
by 3 wk
Pregnant
by 6 wk
Pregnant
by 9 wk
Pregnant
by 12 wk
Pregnant
by 14 wk
90
60
54%
79%
90%
95%
97%
90
48
43%
68%
82%
90%
93%
90
36
32%
54%
69%
79%
83%
80
60
48%
73%
86%
93%
95%
80
48
38%
62%
77%
86%
89%
80
36
29%
49%
64%
74%
79%
70
60
42%
66%
81%
90%
94%
70
48
34%
56%
71%
81%
87%
70
36
25%
44%
58%
69%
74%
Pregnancy rates are the percentage of cows that conceive in a given
breeding period. Pregnancy rates of 80% may be acceptable but above
90% is a good target for a total breeding period, usually between 8 and 14
weeks in length.
2
Submission rate is the proportion of cows that were cyclic and detected in
estrus for insemination
3
Conception rate is the proportion of inseminated cows that conceive.
77
Table 2: Top 10% of active AI Holstein sires (66 of 656 bulls) using different
weighting of traits1
Traits included in
Net Merit$
Wt
%
Ranke
d by
Current
Net
Merit$
Wt
%
Ranked
by
Net
Merit$
2x DPR
Wt
%
Ranked
by
Net
Merit$
3x DPR
Milk
0
1254
0
1198
0
1022
641
Fat
23
60
20
50
17
42
22
Protein
23
42
20
40
17
35
24
Daughter
preg. rate
(DPR)
9
0.4
18
0.9
27
1.3
Somatic cell
score (SCS)
-9
2.84
-8
2.84
-7
2.84
2.86
Productive life
(PL)
17
3.0
14
3.5
11
3.8
3.5
Body size
-4
-6
-8
Udder composite
6
5
4
Feet/legs
3
3
3
Calving ability
6
6
6
100
100
NM$ for top
10% of bulls
$484
100
$460
1
Wt
%
Rank by
DPR
only2
100
1.8
100
$455
$354
Adapted from information via personal communication with Dr. Duane Norman, USDA- AIPL.
2
Net Merit$ among top 10% of bulls based on DPR only whereas the other
columns are based on an index weighting for several traits.
78
Enhanced Early Nutrition for Milk-Fed Calves:
What Can We Expect?
James K. Drackley
Department of Animal Sciences,
University of Illinois at Urbana-Champaign
email: drackley@uiuc.edu
Take Home Messages
-Conventional calf-rearing systems limit nutrient intake from milk or milk replacer
during the first 2-3 weeks of life compared with what calves consume if given
free access to milk. Intensified or accelerated feeding programs provide more
biologically appropriate early growth.
-Accumulated data show little evidence for any detrimental effects of increasing
the amount of milk or milk replacer fed during the preweaning period in calves.
-Subsequent milk production generally has been higher for heifers with improved nutrient status as calves. Some of this effect may be mediated by better
health.
Introduction
Conventional calf-rearing systems typically restrict the amount of milk or
milk replacer fed during the first few weeks of life in an effort to encourage solid
feed intake and allow early weaning. Recent demonstrations of the remarkable
growth improvements in growth and feed efficiency by feeding greater quantities
of milk (Flower and Weary, 2001; Jasper and Weary, 2002) or milk replacer
(Bartlett, 2001; Diaz et al., 2001; Tikofsky et al., 2001; Blome et al., 2003; Bartlett et al., 2006) have stimulated renewed interest in early calf nutrition. To develop a full economic model of the effect of such systems on dairy enterprise
profitability, necessary inputs include effects on growth rates and cost per unit
height or weight increase, effects on subsequent growth after weaning, effects
on health, and effects on subsequent milk production. While data continue to
accumulate in each of these areas, it is not yet possible to prepare a complete
economic assessment.
The purpose of this paper is to provide an overview of intensified early
nutrition programs and data that show negative or positive biological effects.
Interested readers can find more information on several aspects related to intensified early nutrition in recent publications (Drackley, 2005; Drackley and Van
Amburgh, 2005; Van Amburgh and Drackley, 2005).
79
Background
First, what is meant by differences in early nutrition must be established.
Current convention of calf rearing in the U.S. is that calves are fed a limited
amount of milk or milk replacer, typically 8 to 10% of body weight (BW) as liquid,
in an effort to stimulate early consumption of solid feeds (starter). Because volatile fatty acids (particularly butyrate) from fermentation of concentrate-based ingredients are the stimulus for development of the ruminal epithelium, early consumption of starter dry matter (DM) is important for systems in which the goal is
early weaning and the lowest cost rearing program (Davis and Drackley, 1998).
Consumption of this limited amount of solids from milk or milk replacer (typically
400 to 600 g/d) will support maintenance plus average daily gains (ADG) in the
range of 200-300 g/d (for milk replacer) to 300-400 g/d (for whole milk) under
thermoneutral conditions (National Research Council, 2001).However, under
adverse environmental conditions, increased maintenance requirements for
thermogenesis may result in reductions in BW gain or even BW loss. For example, a 45-kg calf consuming 500 g/d of a typical milk replacer powder will lose
BW when the effective environmental temperature is below 5°C (National Research Council, 2001).
Restricted-feeding programs differ markedly from the natural feeding
behavior of calves allowed to suckle their dams or to consume milk ad libitum.
Calves allowed to suckle their mothers typically consume 6 to 10 meals per day,
and may consume 16 to 24% of their BW daily as milk after 3 to 4 wk of age
(Hafez and Lineweaver, 1968). Recent studies have confirmed these patterns in
Holstein calves. Flower and Weary (2001) showed that Holstein calves left with
their dams weighed 59.9 kg at 14 d of age compared with 46.9 kg for calves fed
milk from a bucket at a rate of 10% of BW. Jasper and Weary (2002) reported
mean milk intakes of 8.8 kg/d during the first 35 d of age when Holstein calves
had free access to milk via an artificial teat, compared with 4.7 kg/d for calves
fed milk at 10% of BW. In that experiment, calves with ad libitum access to milk
consumed over 9 kg/d by d 4 of life.
Studies with hand feeding of milk also show that ad libitum intakes of
milk are in excess of 18% of BW. For example, Khouri and Pickering (1968) fed
a milk replacer twice daily to calves during the first 6 wk of life at rates of 11.3,
13.9, 15.9, or 19.4% of BW (ad libitum). The ADG during weeks 2 to 6 of life
were 0.41, 0.50, 0.62, and 0.94 kg/d, respectively. Feed efficiencies (kg milk DM
per kg BW gain) were 1.59, 1.47, 1.33, and 1.23, respectively. The latter values
are very similar to feed efficiencies for young pigs and lambs (Greenwood et al.,
1998; Kim et al., 2001). Consequently, what has been referred to as
“accelerated growth” by calves is, in fact, biologically normal growth. It is a management (i.e., economic) decision to feed smaller amounts of milk or milk replacer twice daily to encourage dry feed intake.
80
As starter intake increases in restricted-milk programs, gains of BW increase and rates of ADG may approach those on more aggressive milk feeding
programs (Figure 1). Thus, differences in plane of nutrition are most pronounced during the first 2-3 wk of life when limit-feeding falls far short of meeting nutrient requirements (National Research Council, 2001). Clearly, early
growth is limited by restricted-milk feeding programs. Because of the close link
between growth and normal developmental processes in animals, it seems wise
to ask what other early-life developmental processes might be limited by our
conventional feeding programs that limit early growth. Consequently, the frame
of reference for the following discussion is the comparison between marginal
nutrition during the first 2-3 wk (from conventional feeding systems or from underfeeding during cold stress) with more biologically appropriate early nutrition.
Figure 1. Example of differences in early growth between calves fed on
a conventional limit-feeding program (milk replacer powder fed at 1.25%
of birth BW; calves weaned at 35 days) or on an intensified program
(milk replacer fed at 2% of birth BW for wk 1, then 2.5% of BW at wk 2
during wk 2-5; calves weaned at d 42). Calves had access to starter
from wk 1 of life. (B.C. Pollard and J.K. Drackley, unpublished data,
2002)
81
Common concerns about intensified early nutrition are unfounded
Although current biologically appropriate early nutrition programs have
not been in existence long enough to make reliable evaluations of longevity,
there is little basis to on which to expect negative effects if properly formulated
and balanced diets are fed to meet nutrient requirements. Some concerns that
have been raised by those accustomed to limit-feeding calves include increased
incidence of scouring and other early health problems, over-fattening, impaired
fertility, decreased milk production (perhaps mediated by impaired mammary
development), bone or skeletal abnormalities at maturity, and, as a result of
some combination of these factors, decreased herd life. Each of these is discussed briefly below.
A common argument in favor of restricted liquid feeding and early weaning has been that scouring is decreased. Fecal consistency becomes less fluid
as dry feed is consumed, primarily as a result of the bulking effect of dietary fiber. However, merely feeding more milk or more of a high-quality milk replacer
does not cause scouring (Mylrea, 1966; Huber et al., 1984; Nocek and Braund,
1986; Appleby et al.,, 2001; Diaz et al., 2001). The occurrence of calf scours,
unless a poor-quality milk replacer containing damaged ingredients is fed, depends more on the load of pathogenic microorganisms in the calf’s environment
(Roy, 1980) and the degree of environmental stress on calves (Bagley, 2001).
Calves fed larger amounts of milk replacer have softer feces, and that requires
a shift of mindset by producers and advisors. Our own experiences with calves
fed milk replacer at up to 18% of BW indicated that average fecal scores were
not significantly different but that days with elevated fecal score (softer feces)
were increased (Bartlett, 2001; Pollard et al., 2003; Bartlett et al., 2006). Feeding milk replacer resulted in softer feces than feeding similar amounts of whole
milk, regardless of the macronutrient composition of the milk replacer (Bartlett,
2001).
Given the known adverse effects of allowing heifers to become too fat
(Sejrsen et al., 2000), concern exists that increased milk or milk replacer might
allow calves to become too fat, in turn impairing subsequent reproduction or
milk production. Our recent studies (Bartlett, 2001; Blome et al., 2003; Bartlett et
al., 2006) as well as those by Van Amburgh and associates (Diaz et al., 2001;
Tikofsky et al., 2001) have shown clearly that body composition can be influenced by dietary composition in young dairy calves. Measurements of stature
increase as the content of dietary crude protein (CP) is increased in isocaloric
diets (i.e., as the dietary protein to energy ratio is increased (Blome et al., 2003;
Bartlett et al., 2006), indicating stimulation of skeletal growth. Whole-body deposition of protein (i.e., lean tissue) also increases linearly as dietary CP supply
increases over a wide range of protein intakes (Figure 2). At the same energy
intake for calves fed isocaloric diets, whole-body protein deposition increases
linearly while at the same time fat deposition decreases linearly (Figure 3) as
the protein to energy ratio increases (Bartlett et al., 2006). Fat deposition is increased by a greater amount of dietary fat compared with a similar amount of
energy from lactose (Bartlett et al., 2001a; Tikofsky et al., 2001). Taken together, these studies indicate that overfattening should not be a concern with
higher protein, moderate-fat milk replacers designed for enhanced growth rates;
fat deposition may increase with larger amounts of whole milk fed for prolonged
periods.
82
While controlled studies of subsequent reproductive characteristics as
affected by early differences in nutrition have not been performed, field observations to date have indicated no problems. Indeed, there is little biological basis
at present to propose that differences in early life nutrition, in the presence of
similar growth from weaning to puberty and breeding, would impact fertility.
Figure 2. Relationship between dietary crude protein intake in milk replacer and whole-body protein deposition in Holstein calves fed milk replacer. (Drawn from data in Bartlett et al., 2006)
83
Over-feeding energy during the period of 3 mo of age to puberty may
negatively impact mammary development and milk production (Sejrsen et al.,
2000). Although concern has been raised that greater liquid feeding early in life
also might impact mammary development, Danish researchers have found no
evidence for effects of high growth rate during the first 2 mo on mammary development (Sejrsen et al., 1998, 2000). Recent research from Michigan State University has shown that improved early nutrition actually stimulated mammary
tissue development (Brown et al., 2005). Calves fed a milk replacer (28.5% CP,
15.0% fat) for ADG of 666 g/d had 32% more parenchymal mass and 47% more
parenchymal DNA than calves fed a conventional milk replacer (20.0% CP,
20.0% fat) for ADG of 379 g/d. In that study, cost of per unit of BW gain was
similar or actually lower for the intensified feeding program.
The author is aware of no evidence that might provide a basis for abnormal skeletal development as a result of greater milk intake in cattle, or any other
mammalian species, during early life. One only has to consider the fact that
beef heifers consume large amounts of milk early in life and live to greater average ages than do dairy cattle, with no evidence of bone problems.
Figure 3. Relationships between whole-body protein deposition and
whole-body fat deposition in Holstein calves fed milk replacers with increasing crude protein content. Reconstituted milk replacers were isocaloric and were fed at a rate of 14% of BW, adjusted weekly. The linear
effect of crude protein content was significant (P < 0.05) for both. (Drawn
from data in Bartlett et al., 2006)
84
Evidence for beneficial impacts of intensified early nutrition is accumulating
Although data are limited yet in many areas there certainly is more evidence that a higher plane of nutrition during early postnatal life provides benefits
to the animal than there is evidence to the contrary.
Intensified early nutrition programs can markedly improve early growth
rates as discussed above. We currently are completing analysis of a large experiment with heifer and bull calves born on the University of Illinois dairy farm
(Stamey and Drackley, 2005, unpublished). The experiment compared a traditional restricted-feeding program of a 20% CP, 20% fat milk replacer with an
intensified step-up feeding program using a 28% CP, 15% fat milk replacer.
Both groups of calves had starter and water available free choice were weaned
at 6 weeks of age. The ADG through 8 wk of age were 20% greater (777 g/d vs.
648 g/d) for the intensified calves. Of greater importance is that gains of withers
height were also about 24% greater for the intensified calves. We will be following these heifers through subsequent growth and first lactation, and hope that
the data will allow a complete economic evaluation of the program.
Israeli researchers (Bar-Peled et al., 1997) compared calves allowed to
suckle nurse cows three times daily for 15 min per feeding during d 5-42 of life
with calves fed a milk replacer (23% CP, 18% fat) in restricted amounts. All
calves had free access to starter concentrate and hay. Suckled calves were
changed to milk replacer at d 43, and the amount fed was decreased to be similar to controls by d 50. From d 51 until calving, management of the two groups
was identical. Suckled calves consumed essentially no starter or hay during the
treatment period, but consumed on average 14% more energy than calves fed
limited amounts of milk replacer. Although ADG were greater during the treatment period (Table 1), suckled calves underwent a pronounced growth slump at
weaning. Consequently, suckled calves were actually nearly 10 kg lighter at 12
wk of age. Nevertheless, suckled calves were 5 cm taller, calved 30 d earlier,
and produced 453 kg more milk in first lactation than calves fed milk replacer in
restricted amounts.
85
Table 1. Growth and subsequent production in Holstein heifers fed restricted
amounts of milk replacer (conventional) or allowed to suckle cows three times
daily during the first 42 d of life (from Bar-Peled et al., 1997).
Variable
Conventional
n
SEM
20
Suckled
SEM
20
BW, kg
6 wk
61.9
3.2
73.4
4.7
12wk
98.2
4.2
88.3
5.1
0 to 6 wk
0.56
0.08
0.85*
0.11
7 to 12 wk
0.86
0.11
0.35*
0.35
0 to 12 wk
0.71
0.10
0.60
0.13
12 wk to conception
0.64
0.08
0.87*
0.09
Conception to calving
Age at conception, d
0.65
0.06
0.67
0.08
426
13
394*
15
Calving age, d
700
15
669*
12
BW at calving, kg
507
24
544
30
ADG, kg/d
†
Milk (kg/300 d)
9171
306
9624
374
Wither height, cm
134.4
1.9
139.7*
2.3
†
* P < 0.05, P < 0.10
A Danish study compared calves fed 4.6 kg of whole milk from birth to
56 d of life with calves allowed to suckle their dam for 30 min twice daily through
56 d (Foldager and Krohn, 1994). Suckled calves produced over 4.5 kg per day
more milk in first lactation than the conventionally fed calves (1403 kg more for
a 305-d lactation). A second Danish study compared calves fed 4.6 kg of whole
milk for 42 d with calves fed ad libitum amounts of milk twice daily from a bucket
through 42 d (Foldager et al., 1997). Calves fed the greater amounts of milk produced 489 kg more milk in first lactation than restricted-fed controls.
86
We recently compared an intensified milk replacer feeding system with a
conventional limit-feeding system with calves born in spring and summer over a
two-year period (Pollard et al., 2003). Feeding rates of the intensified program
varied slightly in the two years and so each year represents a separate trial.
Calves fed the intensified treatments had greater ADG during the milk feeding
period, but stalled markedly around weaning. By 12 wk of age, differences in
BW and stature had narrowed between groups. We did not aggressively breed
heifers based on size. First-lactation 305-day actual milk yields are shown in
Table 2. Early life enhanced feeding resulted in greater milk production during
the first lactation, although the tendency for the diet by trial interaction indicates
that the difference was greater for Trial 1 than Trial 2.
Table 2. First-lactation data for heifers fed either conventional or intensified
milk replacer programs as calves in two trials (Drackley et al., 2007)
Variable
Conventional
Intensified
25.4
24.0
26.5
24.3
1,238
1,243
1,284
1,238
20,340
19,351
23,269
20,104
a
Age at calving (mo)
Trial 1
Trial 2
Calving BW (lb)
Trial 1
Trial 2
305-d milkabc (lb)
Trial 1
Trial 2
a
Trial, P < 0.01.
b
Diet, P < 0.01.
c
Diet × trial, P = 0.13.
Intensified heifers from Trial 1 calved about 1 mo later on average,
were slightly larger, and had greater milk yields. Heifers from both diets in
Trial 2 calved at the same average age and BW, and milk yields differed less.
Regardless of diet, heifers from Trial 2 did not perform as well as those from
Trial 1. This points out the importance of variation from year to year, which
complicates on-farm determination of effects of management changes.
87
The magnitude of the differences in first-lactation milk yield due to improved early nutrition is strikingly similar among the studies that have reported
those results. Given the magnitude of the differences between means and the
degree of variability typically present in experiments of this nature, over 200
cows per treatment would be necessary to have a 90% chance of demonstrating statistical significance at a probability of 0.05! While such large numbers
of animals per treatment would be required in individual experiments to demonstrate effects in later life, data from smaller experiments might be able to be
combined for statistical analysis using techniques such as meta analysis. It is
unfortunate, however, that most research studies on early life nutrition in
calves have not measured subsequent milk production, reproductive efficiency, or longevity. Several studies are ongoing at the time of this writing to
determine longer-term effects of intensified milk replacer programs; watch for
results in the next year.
Poor health during early life is believed to have long-lasting effects on
production and herd life. Epidemiological studies relating specific neonatal
illnesses to later productivity generally have not found strong relationships between any specific illness or condition and subsequent survivability or productivity, although respiratory disease in calves increased the age at first calving
(Correa et al., 1988). Perhaps most interesting is the report that early-life
“dullness” in calves was a significant risk factor for shorter herd life. Calves
that were characterized as having dullness before 90 d of age (defined as dull
appearance, listlessness, droopy ears, and off feed) were 4.3 times more
likely to die after 90 d of age (Curtis et al., 1989) and 1.3 times more likely to
leave the milking herd than herdmates (Warnick et al., 1997). The authors
speculated that this condition might reflect the combined effects of poor health
and suboptimal nutrition.
Insufficiencies of protein or energy are well known to impair health and
immune system function in other species (Woodward, 1998). Is there evidence that inadequate nutrition during early life decreases resistance to disease and compromises health and well being of calves? Williams et al. (1981)
compared calves fed two amounts of milk replacer solids (600 g/d and either
300 or 400 g/d) with either ad libitum or restricted access to calf starter.
Calves fed the higher amount of milk replacer with ad libitum access to starter
had the greatest ADG and least mortality. Other studies have shown that inadequate nutrition results in impaired immune responses in young calves.
Griebel et al. (1987) fed neonatal calves either below maintenance or above
maintenance intakes of milk replacer. Calves fed below maintenance lost BW
and had higher (although nonsignificant) concentrations of cortisol in serum;
lymphocytes isolated from these calves had decreased proliferative responses
compared with adequately fed calves. Malnourished calves had lower primary
antibody response to K99 antigen.
88
Pollock et al. (1993, 1994) compared effects of weaning age (5, 9, or 13
wk of age) and two levels of nutrition (400 g/d or 1000 g/d of milk replacer powder). Weaning at 5 wk resulted in compromised lymphocyte responses (cellular
immunity) at 10 wk of age. The higher plane of nutrition, which was approximately twice maintenance, resulted in improved responses of cell-mediated immunity and decreased skin responses to antigen (Pollock et al., 1993). In contrast, the high plane of nutrition resulted in decreased antibody titres to specific
antigens, without changing total immunoglobulin concentration in serum
(Pollock et al., 1994). These results are consistent with recent evidence demonstrating that neonatal calves have vigorous antigen-specific cell-mediated immune responses but relatively weak antibody responses compared with adult
cattle (Foote et al., 2003; Nonnecke et al., 2003).
Recent research (Nonnecke et al., 2000, 2003) studied immune system
characteristics in calves fed a milk replacer for greater rates of early growth
(30% CP, 20% fat; DM fed at 2.4% of BW) or in calves fed a conventional milk
replacer (20% CP, 20% fat) at slightly greater rates than industry standard (DM
fed at 1.4% of BW). Increased plane of nutrition did not affect total numbers of
blood leucocytes, composition of the mononuclear leukocyte population, mitogen-stimulated DNA synthesis, or immunoglobulin M secretion. However, mononuclear leukocytes isolated from calves fed on the higher plane of nutrition produced more inducible nitric oxide and less interferon-( than cells from conventionally fed calves. In another study by that research group, calves fed 568 g/d
of conventional milk replacer powder (22% CP, 20% fat) had lower antigeninduced proliferation of CD8 lymphocytes than calves fed 1136 g/d of a milk replacer (28% CP, 20% fat) designed for intensified early nutrition (Foote et al.,
2003). While effects were relatively small, it must be remembered that control
calves received adequate nutrients and were under clean and thermoneutral
conditions. Together, available data support a role of nutritional status in at least
some aspects of immune system function in young calves.
Improved neonatal nutritional status might be expected to impact the
immune system via provision of deficient nutrients or energy, or by altering the
endocrine environment (e.g., IGF-1) that affects the developing immune system.
Houdijk et al. (2001) have discussed the partitioning of nutrients among maintenance, immune function, and growth or other productive functions in animals.
These authors raise the possibility that inadequate protein supply may limit
function of the immune system, through the importance of glutamine (and potentially other amino acids). Amino acid status, as indicated particularly by glutamine availability, might be expected to affect both innate and specific immunity.
In addition to its role in protein synthesis, glutamine is a major fuel for rapidly
proliferating cells of the gut (Newsholme et al., 1985b), which might impact barrier function of the intestine in young calves. Glutamine also is a major fuel for
lymphocytes (Newsholme et al., 1985a) and other cells of the immune system
(Calder and Yaqoob, 1999). Deficiency of glutamine results in immunosuppression in other species (Calder and Yaqoob, 1999). Given the importance of protein intake for growth as demonstrated by our experiments (Bartlett et al., 2006;
Blome et al., 2003) in which increasing protein content of isocaloric milk replacers markedly increased ADG and efficiency of gain at similar overall energy retention, relationships among nutrition, growth, and immune function in calves is
an important area.
89
The health status of young calves likely is impacted by interactions of
early nutrition and the environment. Nutritional insufficiency may be especially
problematic for immune function during cold or heat stress, when maintenance
requirements for temperature regulation are increased. For example, we conducted an experiment to determine the value of supplementing milk replacer
with energy sources for Jersey calves raised in hutches during winter (Drackley
et al., 1996). To do so required establishment of an appropriate baseline feeding regimen. Jersey heifer calves fed a conventional milk replacer at 8% of BW
did not maintain BW and had a high incidence of health problems. Calves fed
the same milk replacer at 10% of BW gained small amounts of BW but still were
unhealthy. Only when calves were fed at a rate of 12% of BW were they able to
maintain health and BW gains.
A study conducted in Minnesota (Godden et al., 2005) compared equal
volumes of pasteurized non-saleable milk and a conventional milk replacer. Because whole milk contains about 17% more energy than milk replacer at equal
amounts, indirectly these authors were comparing two planes of nutrition.
Calves fed the pasteurized non-saleable milk had greater ADG than those fed
milk replacer. In summer, mortality of calves did not differ between those fed
milk (2.2%) or milk replacer (2.7%). However, for calves born in the winter, mortality was much greater for calves fed milk replacer (21.0%) than for those fed
milk (2.8%). Much of this difference is likely attributable to the marginal nutrient
status of the calves fed milk replacer because maintenance energy requirements are much greater during cold stress.
Concluding remarks
Current conventional systems restrict nutrient intake during the milk
feeding period in an effort to encourage early intake of calf starter, allow earlier
weaning, and decrease costs of heifer rearing. Programs of more aggressive
liquid feeding early in life result in nutrient intakes that more nearly meet the requirements, in turn allowing normal growth and development. Consequently,
from a biological perspective it would be difficult to argue that improving nutritional status of the young calf during the first few weeks of life should be anything but positive for subsequent productivity and longevity. Properly implemented programs should not appreciably increase, and may in fact decrease,
cost of gain. In fact, as the data continue to accumulate, it is apparent that intensified early nutrition programs may improve subsequent lactation performance.
90
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Dietary Factors Affecting Manure Output in Dairy Cows
William P. Weiss and Juan M. Pinos-Rodríguez
Department of Animal Sciences
Ohio Agricultural Research and Development Center
The Ohio State University, Wooster
Manure is an inevitable byproduct of the production of meat and milk destined
for human consumption. Excessive excretion of manure and manure nutrients represents inefficiencies that increase feed costs, increase the environmental impact of dairy
farming, and increase costs associated with moving and storing manure. Current environmental regulations are usually based on when, where, and how much manure can
be land applied. The ‘where’ and the ‘how much’ are usually based on nitrogen (N) and
phosphorus (P) concentrations in the manure and the soil, and on crop removal rates of
P and N. The primary purpose of this paper is to discuss factors affecting manure output rather than excretion of N and P, but diets that promote high milk production and
just meet requirements for P and N result in the lowest quantities of N and P excreted
per unit of milk produced.
Manure Production by Lactating Cows
Based on research conducted at Ohio State, an average lactating Holstein cow
producing about 70 lbs of milk/day and fed typical Midwestern diets produces about
150 lbs/day of manure (in our measurements, no bedding is used so manure is the sum
of feces and urine) with 12.5% dry matter (DM), 0.59% N, and 0.077% P (Table 1). On
average about one-third of the manure weight was urine and two-thirds feces. In 2006,
the US had about 9 million dairy cows producing 177 billion lbs of milk/year (USDA statistics). Using equations we developed, last year the U.S. dairy herd (excluding replacements) excreted an estimated 493 billion lbs of manure, 2.9 billion lbs of N and
380 million lbs of P. Significant variation in the amount of manure excretion is caused
by feed intake, dietary concentrations of certain nutrients, digestibility, and environmental conditions (e.g., hot weather). We should be able to take advantage of this
variation and formulate diets that result in less manure production.
96
Effects of intake and milk production
Manure output and dry matter intake (DMI) are strongly correlated but
significant variation still occurs (Figure 1). In our data set, manure output varied
by about 75 lb/d within a specific DMI. On average, manure output increased
about 3 lbs/lb of DMI but this relationship was not constant. Increasing DMI
from 35 to 40 lb/day resulted in an increase of 2.7 lb of manure/lb of increased
DMI, but increasing DMI from 55 to 60 lb/day resulted in an average increase of
3.5 lb/day of manure/lb of increased DMI. As intake increases, digestive efficiency tends to decrease because feed passes through the digestive system
quicker. Because water is needed to move digesta, a small decrease in digestibility results in a much larger increase in excretion of manure. If everything else
is equal, we would expect slightly lower digestibility at high intakes resulting in
more manure per pound of intake at high intakes than at lower intakes. Intake
and milk production are correlated and on average high producing cows eat
more than low producing cows. You should not restrict intake so that cows produce less manure because it will also likely reduce milk production. Feeding
diets that are highly digestible results in high milk production at reasonable intakes with reasonable rates of manure excretion. Monitoring feed efficiency (lbs
of fat-corrected milk per lb of DMI) is a means of evaluating diet digestibility.
For most situations, herd average feed efficiency should be around 1.5 to 1.6.
Milk production and manure output are also correlated but the relationship is not strong (Figure 2). This means we can increase milk production without necessarily increasing manure output. Indeed, because cows produce manure even when they are not lactating (80 to 100 lb/day), high producing cows
usually produce less manure per pound of milk than do low producing cows. A
Holstein cow producing 50 lbs of milk averages about 129 lbs of manure (2.6 lbs
of manure/lb of milk) but a Holstein producing 100 lbs of milk produces 175 lbs
of manure or only 1.75 lbs of manure/lb of milk. Increasing milk production is
usually the most effective means of decreasing manure output per unit of milk
produced.
Dietary factors
Corn Silage. The dietary factor that had the greatest effect on manure
production in our data set was the ratio of corn silage to haycrop forage (in our
experiments, alfalfa silage was the predominant haycrop fed). As the percentage of forage that was corn silage increased (resulting in a decrease in the percentage of haycrop forage) urine output decreased substantially, resulting in a
significant decrease in manure output. A 10 percentage unit increase in corn
silage (as percentage of forage) resulted in a decrease in manure output of
about 4 lbs/day.
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The response in total manure we found was essentially the same as reported in
a study from Wisconsin (Wattiaux and Karg, 2004). In our data set, increasing
corn silage decreased urine output but had essentially no effect on fecal output
but in the Wisconsin study increasing corn silage decreased both urine and fecal output. In our studies, cows fed diets with 100% of the forage as haycrop
forage produced about twice as much urine per day as cows fed diets with
100% corn silage. The most likely reason for this effect is differences in potassium concentrations in diets. Corn silage almost always has lower concentrations of potassium than haycrop forages so as corn silage increases and haycrop decreases, dietary concentrations of potassium usually decrease. Any diet
modification that results in lower concentrations of potassium should reduce
manure output. Increasing corn silage in the diet should reduce manure output
but several studies have shown that the ratio of corn silage to haycrop silage
does not affect milk production. Therefore, feeding more corn silage should reduce manure output but have little effect on milk production.
Protein. Increasing the concentration of protein in the diet increases manure output. Manure output by dairy cows increases, on average, about 2 lbs/
day when dietary crude protein concentration increases by 1 percentage unit
(Frank and Swensson, 2002; Wattiaux and Karg, 2004; Weiss and Wyatt,
2006). When diets contain grasses and clover that have very high concentrations of crude protein (and usually high potassium concentrations), manure output may increase even more as diet protein increases (Van Dorland et al.,
2007). On a relative basis, a change in dietary protein has a very large effect
on manure output. A 1 percentage unit change in corn silage would only increase manure output by about 0.4 lbs/day, but a 1 percentage unit change in
crude protein would increase manure output by about 2 lbs/day. However, the
concentration of crude protein in the vast majority of diets fed to dairy cows
probably only varies by 3 or 4 percentage units (i.e., most diets contain between
14 and 18% crude protein). That means the overall impact of changing diet
crude protein on manure output is quite modest. Increasing protein from 14% to
18% would only increase manure output by about 8 lbs/day. On the other hand,
corn silage, as a percent of total forage can range from 0 to 100% so that
changes in corn silage can have a marked effect on manure output
(approximately 40 lbs/day).
Fiber and digestibility. Manure output usually increases as the concentration of dietary fiber (measured as neutral detergent fiber, NDF) increases.
This occurs because, in general, NDF is less digestible than other nutrients. On
average, a 1 percentage unit increase in NDF concentration increases manure
output by 0.5 to 1 lbs/day. Because most diets for lactating cows contain 25 to
35% NDF, the overall effect of varying NDF concentration on manure production
is usually less than 10 lbs/day. Other dietary changes that improve digestibility,
such as feeding corn silage made from brown midrib hybrids, can also reduce
manure output slightly ( about 7 lbs/day) (Weiss and Wyatt, 2006).
98
Manure from Non-lactating Animals
Daily manure output by a dry cow or a growing heifer is much less than
that by a lactating cow (Table 2), but nonlactating animals still contribute to the
manure stream of a dairy farm. Assuming a 2 month dry period, approximately
16% of the adult cows on a typical dairy farm will be in the dry cow group.
Based on average calving intervals, age at first calving, and mortality rates, a
typical farm will also have 80 to 90 replacements/100 adult cows. Assuming a
typical herd makeup and average manure outputs, nonlactating animals produce about 25% of the total manure produced on a farm (Table 3). Therefore,
one method to substantially reduce manure volume on a farm is to move dry
cows and heifers to another location. Dietary factors (corn silage, protein, and
NDF) probably affect manure output by nonlactating animals in a similar fashion
as with lactating cows. However because of the risk of increased metabolic disorders (dry cows), excessive fattening (dry cows and heifers), and feed costs
(dry cows and heifers), nutritionists do not have much leeway to change concentrations of corn silage, protein or NDF so it is unlikely we can greatly change
manure output by these animals. A new method of raising heifers is being investigated at several universities (especially at University of Wisconsin and
Penn State University) that has the potential of substantially reducing manure
output. In this system, heifers are fed a high energy diet but intake is severely
restricted. Animals are fed only enough energy to meet requirements for the
desired rate of gain. Inadequate data are currently available to recommend this
method but that may change in the future.
Conclusions
On average, manure output increases with increased milk production,
however, certain diet modifications should reduce manure output and not affect
milk yield.
•Increasing the concentration of corn silage and reducing the concentration
of haycrop forage should reduce manure output.
•Increasing the concentration of crude protein in a diet increases manure
output. Make sure diets contain adequate but not excessive amounts of
protein.
•Feeding a highly digestible diet reduces manure output. Harvest haycrop
forages at an immature stage and consider growing highly digestible
corn hybrids for silage.
On a typical farm, nonlactating animals (dry cows and replacements) produce
about 25% of the total manure. Moving those animals to another location will
substantially reduce manure volume and should be considered if manure storage volume is limiting. Modifying the diets of these animals probably will not
have a substantial effect on total farm manure output.
99
References
Frank, B., and C. Swensson. 2002. Relationship Between Content of Crude
Protein Rations for Dairy Cows and Milk Yield, Concentration of Urea in
Milk and Ammonia Emissions J. Dairy Sci. 85:1829–1838.
Nennich, T.D., J. H. Harrison, L. M. VanWieringen, D. Meyer, A. J. Heinrichs,
W. P. Weiss, N. R. St-Pierre, R. L. Kincaid, D. L. Davidson, and E.
Block. 2005. Prediction of Manure and Nutrient Excretion from Dairy
Cattle J. Dairy Sci. 88:3721–3733.
Van Dorland, H.A., H.-R. Wettstein, H. Leuenberger, M. Kreuzer. 2007. Effect of
supplementation of fresh and ensiled clovers to ryegrass on nitrogen
loss and methane emission of dairy cows. Livestock Sci. 111: 57–69.
Wattiaux, M.A., K. L. Karg. 2004. Protein Level for Alfalfa and Corn SilageBased Diets: II. Nitrogen Balance and Manure Characteristics. J. Dairy
Sci. 87: 3492–3502.
Weiss, W.P., D. J. Wyatt. 2006. Effect of corn silage hybrid and metabolizable
protein supply on nitrogen metabolism of lactating dairy cows. J. Dairy
Sci. 89:1644–1653.
100
Table 1. Statistics describing Holstein cows and manure output from 15 experiments conducted at Ohio State involving 315 observations and 67 dietary treatments
Measure
Average
Standard Deviation
Dry matter intake, lbs/day
48.2
8.1
Milk yield, lbs/day
68.6
16.0
Wet feces, lbs/day
98.5
21.8
Urine, lbs/day (gallons)
52.4
20.2
Manure, lbs/day
150.9
35.1
Manure dry matter, %
12.5
1.0
Manure nitrogen, %
0.59
0.07
Manure phosphorus, %
0.077
0.017
101
Table 2. Average manure output for various types of Holstein dairy cattle.
Type of cattle
Body weight, Milk, lbs/
lbs
day
DM intake, Manure, lbs/
lbs/day
day
Average lactating
1390
69
47.7
146
High producing cow2
1300
90
53.8
177
Dry cow1
1660
0
22.9
85
Heifer, < 1yr old1
340
0
7.4
27
Heifer, >1 yr old1
960
0
18.3
54
1
2
Data from Nennich et al. (2005).
Data from studies conducted at Ohio State.
102
Table 3. Daily manure production on a typical Holstein dairy farm with
100 lactating cows.
Type of animal Number of
Animals
% of
Herd
Manure, lbs/
day
% of Total Manure
Lactating
cows
100
50
15,000
76
Dry cows
16
8
1360
7
Heifers, <1
year old
44
22
1190
6
Heifers, > 1
year old
40
20
2160
11
Total
200
100
19,710
100
103
300
Manure output, lbs/day
250
200
150
100
50
0
0
20
40
60
80
Dry Matter Intake, lbs/day
Figure 1. Relationship between dry matter intake and manure excretion in lactating and dry Holstein cows. Open squares are data from dry cows, filled diamonds represent lactating cows.
104
300
Manure output, lbs/day
250
200
150
100
50
0
0
50
100
150
Milk yield, lbs/day
Figure 2. Relationship between milk production and manure output in lactating
and dry Holstein cows. Open squares represent data from dry cows, solid diamonds represent data from lactating cows.
105
Cows Under Pressure: Recent Research on Stocking Density, Cow Behavior, and Productivity
Rick Grant
William H. Miner Agricultural Research Institute
Chazy, NY 12921
Phone: 518-846-7121 x116
Email: grant@whminer.com
Dairy Cow’s Daily Time Budget
Essentially, the 24-h time budget represents the net response of a cow to her
environment. Deviations in any herd from these benchmarked behavioral routines represent departures from natural behavior and can serve as a basis for
estimating the performance and economic loss due to poor management strategies. A simplified daily time budget for lactating dairy cattle adapted from Grant
and Albright (2000) for cows in a free-stall environment is:
·
·
·
·
·
·
Eating: 3 to 5 h/d (9 to 14 meals/d)
Lying/resting: 12 to 14 h/d
Social interactions: 2 to 3 h/d
Ruminating: 7 to 10 h/d
Drinking: 30 min/d
Outside pen (milking, travel time): 2.5 to 3.5 h/d
Albright (1993) measured the daily behavioral time budget for a cow (Beecher
Arlinda Ellen) during the lactation in which she set a world record for milk production while housed primarily in a box stall. The data indicated that she spent
6.3 h/d eating, 13.9 h/d resting (lying), and 8 h/d ruminating (7.5 h/d while lying
and 30 min/d while standing). Matzke (2003) compared the time budget of the
top-10% of cows (by milk yield) in a group versus the average time budget for
the entire group of cows and found that the higher producing cows spent 13 to
14 h/d resting whereas the average cows spent 11 to 12 h/d resting. It is interesting that these elite cows, as well as Beecher Arlinda Ellen (the first cow to
produce >50,000 lb of milk in a lactation), both rested for ~14 h/d. One could
speculate that the actual requirement for resting is close to 14 h/d for the most
productive cows, rather than 10 to 12 h/d as commonly proposed. An appropriate analogy might be the strategy of formulating rations to meet the requirements of a cow above the average milk production level in a group of cows. Perhaps we need to consider designing facilities and developing management routines that allow all cows access to stalls for up to 14 h/d; cows requiring less
than this amount will use the time for other behaviors whereas the highest producers will have adequate access to stalls. We have just completed the compilation of 7 years of behavioral data from a variety of experiments at the Institute
and we hope to better define the relationship between resting and other behaviors and productivity, parity, and other factors.
106
It is clear that cows need to accomplish certain natural behavioral activities each
day, and we cannot allow our management routines to interfere. If we tally up
the required number of hours each day to satisfy the basic behavioral needs, it
approaches 21.5 h/d. Given this absolute time need, it is easy to see how our
management practices can very easily perturb the cow’s normal time budget. In
fact, if cows are kept outside of the pen and denied access to resources such as
stalls, feed, and water for greater than approximately 3.5 h/d, then they will be
forced to give up some other activity since there are only 24 hours in a day. Often, resting time or feeding time will be reduced with negative consequences for
productivity and health. Improper grouping strategies that result in overcrowding
and excessive time in holding pens are two common ways of upsetting the time
budget and thereby reducing herd productivity.
Natural Behavioral Needs of Dairy Cattle
Cows have a strong behavioral need to rest. Recently, Jensen et al. (2004)
demonstrated that cows have a very strong motivation to rest, and that this motivation to rest increases as the length of rest deprivation becomes greater. In
fact, lying behavior has a high priority for cattle after relatively short periods of
lying deprivation. Cows have a definite requirement for resting (lying down) that
they attempt to achieve, even if it means giving up some feeding time. A key
concept is that feeding and resting behavior are linked in dairy cattle. Numerous
studies show that management factors that interfere with resting inevitably reduce feeding behavior as well. A classic paper published by Metz (1985) evaluated what cows would do when access to either rest (stalls) or feed (manger)
was prohibited. Cows attempt to maintain a rather fixed amount of lying time,
and their well-being is impaired when lying time is restricted for several hours
(Metz, 1985). When lying and eating are restricted simultaneously, cows choose
to rest rather than eat, with an additional 1.5 h/d standing time associated with a
45-min reduction in feeding time (Metz, 1985). A similar relationship was observed by Batchelder (2000) where cows with a stocking density of 130% preferred using free stalls versus eating post-milking and spent more time in the
alley waiting to lie down than eating when compared with a stocking density of
100%. We have observed similar responses in dairy cows in a recent study
here at Miner Institute at ~130% and ~145% stocking density (Hill et al., 2006).
Resting and feeding behavior are even linked during the transition period. Firstcalf heifers and mature cows that had greater lying and ruminating activity on
days -2 and -6 prepartum also had greater feed intake and milk yield during
days 1 to 14 postpartum (Daniels et al., 2003). This relationship raises an important question: how do we motivate cows to rest and ruminate during the
close-up period?
Cows require 12 to 14 hours/day of rest (lying down). Benefits of resting include:
potentially greater milk synthesis due to greater blood flow through the udder,
greater blood flow to the gravid uterus during late lactation, increased rumination effectiveness, less stress on the hoof and less lameness, less fatigue
stress, and greater feed intake. Grant (2004) has proposed that each additional
one hour of resting time translates into 2 to 3.5 more pounds of milk per cow
daily.
107
The bottom line is that lying has a higher priority than eating and social interactions for both early and late lactation dairy cows, and that cows compensate for
reduced access to resting by spending less time eating to free up time for making up lost resting activity (Munksgaard et al., 2005). Interestingly, although little
time is allocated to social contact with other cows, under conditions of limited
access to feed and stalls, cows still defend their ability to have some social interactions – showing that they are social creatures.
Cows have a naturally aggressive feeding drive. The naturally aggressive feeding drive of lactating dairy cows was best described by Dado and Allen (1994)
when they concluded that higher producing (and typically older cows) eat more
feed, eat larger meals more quickly, ruminate more efficiently, and drink more
water more quickly than lower producing (and typically younger cows). Some
competition for feed is inevitable with dairy cows. Even with unlimited access to
feed, cows interact in ways that give some cows an advantage over others
(Oloffson, 1999).
A study conducted in 1998 provides the best illustration of the dairy cow’s naturally aggressive feeding drive. In this study (Hansen and Pallesen, 1998) researchers measured the force applied to the feed barrier during eating. They
observed that cows willingly exert greater than 500 pounds of force against the
feed barrier in an attempt to reach as much feed in the bunk as possible. Pressure in excess of 225 pounds is sufficient to cause acute tissue damage – so
cows will exert enough pressure to cause injury when trying to reach feed. This
is perhaps the best illustration of the dairy cow’s naturally aggressive feeding
drive. We need to manage the feeding area and feed delivery system so that
the cow does not need to exert these levels of force against the feed barrier
while reaching for feed.
Grouping Strategies and Natural Behavioral Responses
Recently, Boe and Faerevik (2003) published an excellent review of grouping
and social responses in calves, heifers, and mature cows. Previously, Grant and
Albright (2001) published a review specifically on effects of grouping strategy on
feed intake in dairy cattle. A fundamental consideration for any decision tool on
grouping strategies is the difference between conventional concepts in dominance hierarchies and grouping and what may be closer to reality. Conventionally, it is assumed that 1) cows fight to establish social hierarchy, 2) fighting
stops once hierarchy is established, 3) dominant cows regulate access to the
resources, 4) group size should not exceed number of cows an individual can
recognize, 5) dominance hierarchy is rapidly established – 50% within one hour,
and 6) the hierarchy is stable (only 4% are reversed). Contrast this rather static
depiction of group interactions with the following more dynamic and likely realistic scenario: 1) continued and fluctuating levels of fighting/aggression, 2) formation of subgroups within larger pens, 3) inability to recognize all peers when
group size exceeds approximately 100 cows, 4) some individuals thrive, not by
winning fights, but by not participating, and 5) stable hierarchy formed within 2 d
for cows with previous social experience and within 4 d for cows with no previous experience.
108
Achievement of social stability in a group of cattle is defined as when nonphysical agonistic interactions among group members predominate, and the ratio of
physical to nonphysical interactions remains comparatively stable (Kondo and
Hurnik, 1990). Various social behaviors and locomotor activity will return to a
baseline level within 5 to 15 d following a grouping change such as regrouping
or commingling (Boe and Faerevik, 2003). Essentially, this represents the major
challenge inherent in grouping cattle. We need to manage a group of cows such
that the rate of decline in physical interactions is as rapid as possible, and that
the period of social stability is maximized. Realistically, animals move into and
out of pens continuously on many farms, and so the challenge becomes managing the magnitude of increase in the physical interactions that accompany any
regrouping and introduction of new animals into a pen. An especially good example of this continuously changing group situation is the fresh pen. A reasonable analogy would be steady state conditions in the rumen – they are never
truly achieved, just assumed.
Early decision-support tools to help with grouping decisions may assume that
social stability is reached and then is maintained, but this would clearly be simplification of reality. Monitoring and then devising means to control the physical:nonphysical interaction ratio would be a valuable tool for producers and consultants. Classic data such as that reported by Krohn and Konggard (1980; cited
in Grant and Albright, 2001) provides useful information for modeling changes in
resting, feeding, and other activity that occurs over time with regrouping. We
need similar data from cows managed in larger groups.
Stocking Density and Cow Behavioral Responses
Stocking density will affect the time budget of dairy cattle. To date, few experiments have evaluated stocking density, and most were conducted using small
numbers of animals per pen. Consequently, the real effect of stocking density
on larger group sizes remains unknown. A key difference between small group
sizes and larger (more realistic) group sizes is the amount of time that an animal
will spend outside the pen for milking and other management procedures. When
cows spend too much time away from the pen (basically more than 3.5 h/d),
resting time will be reduced (Matzke et al., 2002). Additionally, when primi- and
multiparous animals are commingled, resting time is reduced much more for the
heifers than for older cows (-2.6 h/d for multiparous cows and –4.2 h/d for primiparous cows; Matzke, 2003).
109
The influence of stocking density of dairy cow behavior from the few reports in
the literature has been summarized by Grant (2003). Although there is clearly
variation among studies, the few data reported thus far are surprisingly consistent. One point of difference is between Wierenga and Hopster (1990) and the
other reports for the effect of stocking density on resting. They found relatively
little impact of overstocking on resting, which differs substantially from other reports. Some tentative conclusions to draw from these studies are: 1) at 120%
stocking density and beyond, resting time is reduced by 12 to 27% (may be a
function of pen size with greater reduction for larger pens), 2) eating time is not
affected greatly by stocking density (although meal patterns and feed intake
may well be), 3) rumination may be reduced by as much as 25% at 130% stocking density, and 4) at 120% stocking density or greater, standing time will be
increased by 15 to 25%. In general, the negative effect of overstocking beyond
~120% on resting and standing becomes more pronounced as the level increases, but there is insufficient data with larger group sizes to accurately model
the effect at this point.
Grouping of Cows and Heifers
Most of us are aware of the recommendation to group first-lactation heifers
separately from mature cows. Various studies have shown that heifers housed
separately have greater dry matter intake and higher productivity than those
housed in mixed groups, but why is this? Research from the 1970s showed a
10 to 15% improvement in eating and milk yield when first-calf heifers were
grouped separately from older cows. There was a nearly 20% increase in resting activity when heifers were housed separately.
The common thinking is that, since heifers are smaller, they have more difficulty
competing for feed. While this is often true, recent research has shown that
there are actually many more differences between heifers and mature cows
than we may have suspected.
For example, heifers take smaller bites and spend more time feeding than mature cows. Since mature cows are usually more dominant and can push heifers
away from feeding spaces, grouping them separately may ensure that heifers
have enough time to feed throughout the day. Recent Spanish work found that
heifers grouped separately ruminate more and drink more. A companion study
to this work published in the January issue of the Journal of Dairy Science
(Bach et al., 2006) indicated that housing heifers separately may also provide
the added benefits of increased efficiency of fat-corrected milk production and
less body weight loss in the first month of lactation. The improvement in milk fat
production might be associated with both the increase in rumination and greater
number of meals per day observed in heifer-only groups.
110
Resting behavior can also be affected in mixed groups. Cows do not perceive
all stalls equally. Research has shown that dominant, mature cows will lie in
stalls nearest the feed manger, while heifers tend to lie in stalls along the back
wall. The heifers that do lie in the stalls nearest the feed bunk ruminate less
than those lying along the outside wall, perhaps indicating that they are stressed
by the thought that an older cow might kick them out at any time. British researchers have also observed signs of stress exhibited by heifers in mixed
groups such as more time spent fighting and grooming than heifers grouped
separately.
Grouping heifers separately is particularly important in overcrowded situations.
Subordinate animals are the first to be affected as stocking rates increase beyond 100%. Although we need to study it further, here at Miner Institute we recently found that increased stocking rates reduced time spent lying by heifers
more than cows. It also appears that heifers decrease rumination more than
cows as stocking rate increases, which complements the research mentioned
earlier. If our results prove true, reduced rumination and a possible increase in
feeding rate may result in acidosis. Combined with increased time spent standing, this could create a perfect storm and increase lameness in heifers just as
we want them to start paying off all of the costs we just put into raising them.
We also observed a potential decrease of up to 18 pounds of milk per day for
the heifers compared with the cows as the stocking rate increased to 131 and
142%. It will take a long time for a heifer to pay for herself with that extent of
reduction in milk yield.
Stocking Density, Cow Behavior, and Performance during Transition Period
Research published during the past years illustrates the importance of creating
the right environment for the
transition cows in order to motivate them to be productive and healthy herd
members. Major factors to consider are the natural behavioral patterns of transition cows, stocking rate, and grouping strategy of the close-up and fresh cow
pens. Feeding, resting, and ruminating activity all decrease, and standing time
increases, right at parturition. Also, we need to focus on the time spent managing transition cows. That time typically increases from virtually none to as much
as several hours after calving. We need to keep in mind that cows cannot be out
of their pens and away from their resources for more than 3.5 h/d or else they
will be forced to take time out of required activities such as resting or eating.
Researchers at the University of Wisconsin Veterinary School evaluated the effect of overcrowding on the prefresh, close-up pen. In their study, the pens contained both first-calf heifers and older cows. When stocking density was greater
than 80% of stalls in the prefresh group of mixed cows and heifers, milk yield
was reduced for the heifers during the first 83 days in milk following calving. In
fact, for each 10% increase in prefresh 90%.
111
Also, on-farm observations from Idaho showed a strong negative relationship
between headlock stocking density in the close-up pen and incidence of abomasal displacements after calving (Kluth, 2005, personal communication). Whenever headlock stocking density was greater than 90%, then the incidence of
DA’s went up sharply. Clearly, the take-home message of this research is that
stocking density greater than 80 to 90% in the prefresh or close-up pen will result in lost milk production and greater fresh-cow health problems.
In the fresh-cow pen, there is less research, but still an indication that stocking
densities less than 100% for both stalls and manger space will result in better
feed intake, milk yield, and fewer health problems. Also, keeping first-calf heifers grouped separately from older cows in both the prefresh and postfresh pens
will help to ensure better health and productivity of the first-lactation animals.
For cows beyond the fresh group, there is not as much information, but the data
definitely show that beyond 120% overstocking of stalls that resting behavior
usually drops off substantially. No doubt, there is considerable variability among
farms, but if we are stocking are pens beyond 120%, then red flags need to be
raised that a problem is much more likely.
For the transition period, monitoring milk yield can be a useful indicator of the
overall effectiveness of the management system. Useful targets for both firstcalf and mature cows for milk yield are:
·
First lactation animals: target would be to observe an 8% increase in
milk per day for the first 18 days of lactation. A problem exists if there is
no increase in milk or milk yield is less than 65 pounds per day at 30
days in milk.
·
For second and greater lactation animals, there should be a 10% increase in milk yield per day during the first 14 days of lactation. A problem exists if there is no increase in milk yield or if milk production is less
than 85 pounds per day at 30 days in milk.
The bottom line is that stocking density of the transition pens is a key part of the
management strategy. We have suspected this for a long while and now we
have good evidence that we lose milk and suffer more health problems when
we overstock the close-up and fresh cow pens. In fact, even 100% stocking rate
is too high!
Recent Research on Stocking Density at Miner Institute
We have just finished a study at Miner Institute that evaluated the effect of 100,
115, 130, or 145% stocking density of stalls and manger space on production
and behavior. The various stocking densities were obtained by chaining off
stalls or closing headlocks. So, alley space remained constant which may have
softened the effect of overstocking that we observed.
112
Overall, we observed that lying time was reduced by 1.1 hours/day when stocking density increased from 100 to 145%. At the same time, milk yield dropped
numerically from 94.6 to 91.3 pounds/day. Interestingly, this 3.3 lb/day difference in milk yield agreed well with a large data set that we had pulled together
last year from behavior research here at Miner where we found that each onehour change in resting time was associated with a 3.5 pound/day change in milk
yield. Of course, it could all be coincidence, but I really believe that the relationship between resting and milk yield is real.
As stocking rate increased, standing time in the alleys increased and time spent
ruminating while lying decreased. Interestingly, total feeding time was unaffected and averaged about 5 hours/day. What we couldn’t measure in our study
was rate of eating, and I suspect that this increased as stocking rate increased.
Things became even more interesting when we looked at the differential response of first-lactation versus older cows and lame versus sound cows. As
stocking density increased, the difference in milk yield between younger and
older cows grew from 6 pounds/day at 100% stocking rate up to nearly 15
pounds/day at higher stocking rates.
As stocking rate increased, the milk yield of lame cows was markedly reduced
compared with sound cows. From 100% up to 130% stocking rate, the difference between sound and lame cows in milk yield increased by 26 pounds/day.
At 145% stocking rate, the difference between sound and lame cows narrowed
because the milk yield of sound cows suffered at this higher degree of stocking.
As stocking rate increased to 145%, lying time of lame cows was reduced by
one hour and ruminating time was reduced by nearly one hour as well.
With some assumptions and measures from our Institute herd, I made a rough
calculation of margin per cow based on the results observed in this study. Even
though they are tentative, the calculations point out an interesting trend which I
believe would track well with the real-world situation. The margin per cow was
similar between 100 and 115% stocking rate (actually it was very slightly greater
at 115%), it dropped off substantially at 130%, and really nosedived at 145%.
Obviously, this response will differ by farm and the management practices employed. But, these data do agree extremely well with the handful of reported
studies that indicate that things become interesting somewhere around 120%
stocking rate.
Stocking Density for Heifers
Overcrowding research in growing heifers is nonexistent at this point. There is
just beginning to be some good work that documents behavioral and productive
responses to overcrowding during the transition period and later stages of lactation.
113
One paper from Penn State evaluated the effect of reducing feed bunk length
on growing heifer response (Longenbach et al., 1999). Based on higher growth
rates and maintenance of natural feeding behaviors, they concluded:
·
·
·
5.9-in feed bunk space is appropriate for heifers 4 to 8 month of age;
12.2-in feed bunk space for heifers 11.5 to 15.5 month of age;
18.5-feed bunk space for heifers 17 to 21 months of age.
Reduction in feed bunk length significantly affected feeding behavior for all three
age categories with increased competition for feed, less stable group social
structure, and greater variation in live weight gains with greater overcrowding of
the feed bunk. A key point of the study was that overcrowding the bunk did not
necessarily impact overall pen growth rate, but it did affect individual animal
growth rates with subordinate heifers gaining less than the more dominant heifers. In the authors words "At these (recommended) feed bunk lengths, the heifers are in a more harmonious group housing environment that allows them to
achieve the body weight gains and skeletal growth necessary to achieve calving
at 22 to 24 months of age."
Other than this study, I don't know of any other controlled research studies.
There is some field evidence that feeding behaviors learned as a growing heifer
(such as slug feeding under conditions of limited feed availability and excessive
competition) may carry over into the lactation period where it could be very detrimental to her health. Solid research evidence is lacking for this idea, but it is
definitely possible on some farms.
Time Budget Evaluator
We have developed a “Time Budget Evaluator” at Miner Institute as an initial
attempt at predicting the impact of management routines and stocking density
on the time budget of dairy cows. The targets for resting and eating activity are
based on data to-date from larger pen studies as well as more carefully controlled research with smaller group sizes. Although a range exists in measured
eating time (3 to 6 h/d) we have chosen 5.5 h/d for this version, although this
value can be changed by the user for any given situation. Time spent outside
the pen for the milking process and any other activities may also be entered.
Similar to eating time, commonly observed times for drinking and standing are
incorporated into the spreadsheet, but the user may adjust these values if desired. These inputs allow calculation of time available for resting for a specific
situation. This approach is simplistic because it forces the user to either measure, estimate, or accept standard values for eating, drinking, and other activities.
As more research is generated, hopefully we will be able to better predict or
more easily measure these inputs on-farm.
114
The spreadsheet also adjusts lying and standing time based on stocking density
of the stalls. Because there is very little data, particularly for larger group sizes,
the current version of the spreadsheet simply adjusts lying and standing at
120% stocking density. This is an oversimplification of reality, but there is insufficient data to warrant a more detailed approach. The spreadsheet then subtracts the resting time available for the group from the requirement for resting for
both average cows and the highest producing cows in the group (based on data
by Matzke, 2003). If the difference is negative (i.e. resting time is deficient), then
a predicted milk production loss is predicted using the relationship of one additional hour lying time beyond 7 h/d is associated with 2 lb/cow/d more milk. As
previously discussed, this approach simplifies what may well be very complicated impacts on herd health into a single estimate of milk production loss. In
field tests, in troubleshooting situations during the past several years, the
spreadsheet has proven remarkably accurate at predicting lost milk production
on-farm. The final calculation of the spreadsheet simply converts the energy
contained in the lost milk yield to the equivalent loss in body weight or condition
score. Note that this is simply an equivalent energy calculation, and that there is
no published research relating resting time directly to body condition score
changes. At the bottom of the spreadsheet, there are calculations of potential
losses in milk yield for first-calf heifers and lame cows in mixed groups based on
the results of our overcrowding study discussed earlier.
The Excel spreadsheet is available at the Miner Agricultural Institute web site:
http://www.whminer.org.
Summary
Considerably more research is required to develop accurate tools to evaluate
management strategies to minimize negative effects on natural behaviors and
time budgets. Key information would include measurement of feed intake and
feeding behavior for cows that are group-housed in competitive situations. Resting and standing time play a major role in cow health and productivity and effects of management on these two variables must be understood. A simple
spreadsheet is presented to assess the time budget for cows on-farm, both as a
tool for cautious use and to determine areas requiring further research.
115
Selected References
Albright, J. L. 1993. Feeding behavior in dairy cattle. J. Dairy Sci. 76:485.
Bach, A., C. Iglesias, and I. Busto. 2006. A computerized system for monitoring
feeding behavior and individual feed intake of dairy cattle in loosehoused conditions. J. Dairy Sci. 87:358(Abstr.)
Batchelder, T. L. 2000. The impact of head gates and overcrowding on production and behavior patterns of lactating dairy cows. In Dairy Housing and
Equipment Systems. Managing and Planning for Profitability. Natural
Resource, Agriculture, and Engineering Service Publ. 129. Camp Hill,
PA.
Boe, K. E., and G Faerevik. 2003. Grouping and social preferences in calves,
heifers, and cows. Appl. Anim. Behav. Sci. 80:175-190.
Dado, R. G., and M. S. Allen. 1994. Variation in and relationships among feeding, chewing, and drinking variables for lactating dairy cows. J. Dairy Sci.
77:132-144.
DeVries, T. J., M.A.G. von Keyserlingk, and D. M. Weary. 2004. Effect of feeding space on the inter-cow distance, aggression, and feeding behavior of
free-stall housed dairy cows. J. Dairy Sci. 87:1432-1438.
DeVries, T. J., M.A.G. von Keyserlingk, and K. A. Beauchemin. 2003. Diurnal
feeding pattern of lactating dairy cows. J. Dairy Sci. 86:4079-4082.
Grant, R. J. 1999. Management eye on the cow: Taking advantage of cow behavior. Page 39 in Proc. Tri-State Dairy Management Conference. November 10-11, Fort Wayne, IN.
Grant, R. J. 2003. Taking advantage of dairy cow behavior: cost of ignoring time
budgets. In Proc. 2003 Cornell Nutr. Conf. For Feed Manufac. October
21-23. Cornell University. Wyndham Syracuse Hotel. Syracuse, NY.
Grant, R. J., and J. L. Albright. 2000. Feeding behaviour. In Farm Animal Metabolism and Nutrition. J.P.F. D’Mello, ed. CABI Publishing. New York,
NY.
Grant, R. J., and J. L. Albright. 2001. Effect of animal grouping on feeding behavior and intake of dairy cattle. J. Dairy Sci. 84:E156-E163.
Kondo, S., and J. F. Hurnik. 1990. Stabilization of social hierarchy in dairy cows.
Appl. Anim. Behav. Sci. 27:287-297.
116
Kondo, S., J. Sekine, M. Okubo, and Y. Asahida. 1989. The effect of group size
and space allowance on the agonistic and spacing behavior of cattle.
Appl. Anim. Behav. Sci. 24:127-135.
Matzke, W. C. 2003. Behavior of large groups of lactating dairy cattle housed in
a free stall barn. M.S. Thesis. Univ. of Nebraska, Lincoln.
Matzke, W. C., and R. J. Grant. 2002. Behavior of primi- and multiparous lactating dairy cattle in commingled groups. J. Dairy Sci. 85:372(Abstr.)
Metz, J.H.M. 1985. The reaction of cows to short-term deprivation of lying.
Appl. Anim. Behav. Sci. 13:310.
Olofsson, J. 1999. Competition for total mixed diets fed for ad libitum intake using one or four cows per feeding station. J. Dairy Sci. 82:69-79.
117
Let There Be Light: Photoperiod Management of Dairy Cattle
Geoffrey E. Dahl, Ph.D.
Department of Animal Sciences
University of Florida
352-392-1981
gdahl@ufl.edu
Introduction
Photoperiod is the duration of light that an animal is exposed to in a day. It is
often manipulated artificially to produce either long days, which are 16 to 18 hr
of light and 6 to 8 hr of darkness, or short days, which is characterized by 8 hr of
light and 16 hr of darkness. Photoperiod affects animal physiology in a number
of ways, for example, growth, lactation and reproduction are all affected by light
exposure in cattle. This paper provides a brief review of how photoperiod can
be managed across the life cycle of a cow to improve performance and health.
Exposure to variable light and dark cycles alters the secretion of hormones, and
ultimately it is those endocrine fluctuations that cause production responses.
The first impact of light exposure is on secretion of the hormone melatonin,
which is suppressed by light. In contrast, darkness is associated with a rapid
and robust increase in the secretion of melatonin. Thus, cattle and other animals use the duration of elevated melatonin as a signal for physiological
daylength.
The pattern of melatonin release drives changes in the secretion of other hormones. Two of the hormones critical to the discussion of photoperiodic responses in cattle are insulin-like growth factor-I (IGF-I) and prolactin (PRL)
(Dahl et al, 2000). Increases in IGF-I are associated with increases in milk yield
when cows are treated with bovine somatotropin, and there is evidence that
IGF-I affects mammary cell function. PRL has numerous physiological actions,
but most notable are the affects on mammary growth and the immune system.
Under long day photoperiod, blood concentrations of IGF-I and PRL increase
relative to short days. These hormonal shifts are the basis for changes in lactation, growth and health in cattle when housed in different photoperiods.
118
Long day effects on Lactation
During lactation, exposure to long days increases milk yield in cattle an average
of 5 lbs of milk/day (Peters et al., 1978; Stanisiewski et al., 1985), and the
increase is associated with an increase in IGF-I (Dahl et al., 1997; 2000). The
boost in milk yield occurs regardless of stage of lactation or parity. Milk
production increases gradually over 2 to 4 weeks and it drives an increase in
feed intake of 2 to 3 lbs. of dry matter each day. There is generally no change
in milk composition, although occasional reports of slight decreases in milkfat
have appeared (Dahl and Petitclerc, 2003). Long days can also be combined
with other production enhancers, such as bST for additive effect (Miller et al.,
2000).
Given the benefit of increasing the duration of light exposure in lactating cows,
an obvious question is how to manage that photoperiod properly. The target
light intensity for the 16 to 18 hrs of light is 15 to 20 footcandles. That level of
illumination can be achieved with a variety of lamps, from fluorescent to metal
halide to high-pressure sodium vapor lamps. However, lamps should be
selected based on the mounting height available, which is dependent on the
barn type. The most efficient lamp that can be mounted in your facility, based
on ceiling or truss height, should be selected. It is important to note that these
same considerations for lighting system design apply to photoperiod
management for dry cows and growing heifers.
Lighting Effects in Dry Cows
Photoperiod management also has significant effects on cows during the dry
period. In contrast to lactating cows, however, exposure to short days offers the
treatment that produces the greatest benefit to production and health.
Specifically, dry cows housed under short days produce an average of 7 lbs
milk/day relative to cows under long days when dry (Miller et al., 1999;
Auchtung et al., 2005). This response is independent of photoperiod exposure
after calving, in fact most studies have not provided any additional lighting
during lactation.
Cows on short days experience a decrease in circulating PRL, but the
expression of the receptor for PRL increases (Auchtung et al., 2003; 2004a).
Therefore, the PRL signal is amplified and at the mammary gland this translates
to an increase in mammary growth (Wall et al., 2005). Of perhaps greater
interest to producers are the effects on health during the transition period in dry
cows under short days. The altered PRL signaling affects immune cell function
in a positive manner, and dry cows on short days had reduced somatic cell
counts at calving compared with cows on long days (Auchtung et al. 2004b). In
that same study cows on short days had fewer new quarter infections in early
lactation. Thus, short days appear to improve mammary health in addition to
the effect on production.
119
Photoperiod for growing animals
In addition to the effects described above for mature cows, heifers on long days
from weaning to puberty grow at a faster rate than those on short days (Rius et
al., 2005). Most of the growth increase is in height, and the long day heifers
tend to be leaner than the heifers on short days. The long day heifers remained
taller when height was followed through to calving. Because height is more
strongly correlated to future production than weight, this early growth response
should be an advantage. Indeed, when heifers exposed to long days during the
prepubertal period were tracked through calving and into their first lactation,
they produced over 1600 lbs. more milk than heifers that were raised on short
days prepubertally (Rius and Dahl, 2006).
Heifers on long days also achieve puberty sooner than those on short days;
typically a month or so earlier (Hansen, 1985). Like the effect on growth, this
response should be an advantage as there is evidence that increasing the number of cycles before breeding results in higher conception rates. Thus, there is
no biological disadvantage to the use of long days to speed heifer development.
An economic analysis has not been completed to examine the returns for long
day exposure of growing heifers. However, using a few careful assumptions it
is possible to predict if such a management approach is reasonable. Given the
milk yield response of approximately 16 cwt. in the first lactation of heifers
grown under long days, a conservative estimate of an extra $200 in income in
that first lactation can be made. The period between weaning and puberty is
approximately 200 days for dairy heifers, so the cost of lighting would have to
be greater than $1/heifer/day for a loss to be avoided. Therefore, it is likely that
treatment with long days would be cost effective in many heifer growing situations.
Summary
The preceding evidence supports the concept that long day exposure improves
milk production during lactation. Further, raising heifers under long days improves growth and ultimately first lactation milk yield. In contrast dry cows
housed under short days have higher production and health in the subsequent
lactation. The hormonal basis for these responses are linked to IGF-I during
lactation and growth, and PRL during the dry period. Photoperiod management
of dairy cattle is a simple technique that can be used to improve production efficiency and profitability across growth, lactation and the dry period.
120
References
Auchtung, T.L., P.E. Kendall, J. Salak-Johnson, T.B. McFadden and G.E. Dahl.
2003. Photoperiod and bromocriptine treatment effects on expression
of prolactin receptor mRNA in bovine liver, mammary gland and peripheral blood lymphocytes. J. Endocrinol. 179:347-356.
Auchtung, T.L. and G.E. Dahl. 2004a. Prolactin mediates photoperiodic immune enhancement: Effects of administration of exogenous prolactin
on circulating concentrations, receptor expression, and immune function in steers. Biol. Reprod. 71:1913-1918.
Auchtung, T.L., J.L. Salak-Johnson, D.E. Morin, C.C. Mallard, and G.E. Dahl.
2004b. Effects of photoperiod during the dry period on cellular immune
function of dairy cows. J. Dairy Sci. 87:3683-3689.
Auchtung, T.L., A.G. Rius, P.E. Kendall, T.B. McFadden and G.E. Dahl. 2005.
Effects of photoperiod during the dry period on prolactin, prolactin receptor and milk production of dairy cows. J. Dairy Sci. 88: 121-127.
Dahl, G.E., T.H. Elsasser, A.V. Capuco, R.A. Erdman and R.R. Peters. 1997.
Effects of long daily photoperiod on milk yield and circulating insulinlike growth factor-1 (IGF-1). J. Dairy Sci. 80:2784-2789.
Dahl, G.E., B.A. Buchanan and H.A. Tucker. 2000. Photoperiodic effects on
dairy cattle: A review. J. Dairy Sci. 83:885-893.
Dahl, G.E. and D. Petitclerc. 2003. Management of photoperiod in the dairy
herd for improved production and health. J. Anim. Sci. 81(Suppl.
3):11-17.
Hansen, P. J. 1985. Seasonal modulation of puberty and the postpartum
anestrus in cattle: a review. Livest. Prod. Sci. 12:309-327.
Kendall, P.E., T.L. Auchtung, K.S. Swanson, R.P. Radcliff, M.C. Lucy, J.K.
Drackley and G.E. Dahl. 2003. Effect of photoperiod on hepatic
growth hormone receptor 1A expression in steer calves. J. Anim. Sci.
81:1440-1446.
Miller, A.R.E., E.P. Stanisiewski, R.A. Erdman, L.W. Douglass and G.E. Dahl.
1999. Effects of long daily photoperiod and bovine somatotropin
(Trobest®) on milk yield in cattle. J. Dairy Sci. 82:1716-1722.
121
Miller, A.R.E., L.W. Douglass, R.A. Erdman and G.E. Dahl. 2000. Effects of
photoperiodic manipulation during the dry period of dairy cows. J.
Dairy Sci. 83:962-967.
Peters, R. R., L. T. Chapin, K. B. Leining, and H. A. Tucker. 1978. Supplemental lighting stimulates growth and lactation in cattle.
Science
(Washington, DC) 199:911-912.
Rius, A.G., E.E. Connor, A.V. Capuco, P.E. Kendall, T.L. AuchtungMontgomery, and G.E. Dahl. 2005. Long day photoperiod that enhances puberty does not limit body growth in Holstein heifers. J.
Dairy Sci. 88:4356-4365.
Rius, A.G. and G.E. Dahl. 2006. Short communication: Exposure to long day
photoperiod prepubertally increases milk yield in primiparous heifers.
J. Dairy Sci. 89:2080-2083.
Stanisiewski, E. P., R. W. Mellenberger, C. R. Anderson, and H. A. Tucker.
1985. Effect of photoperiod on milk yield and milk fat in commercial
dairy herds. J. Dairy Sci. 68:1134-1140.
Wall, E.H., T.L. Auchtung, G.E. Dahl, S.E. Ellis and T.B. McFadden. 2005. Exposure to short day photoperiod enhances mammary growth during
the dry period of dairy cows. J. Dairy Sci. 88:1994-2003.
122