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2010 Dairy Cattle Reproduction Council Annual Meeting
MANAGING AND MONITORING FRESH COWSFOR IMPROVED REPRODUCTIVE SUCCESS
Michael Overton, DVM, MPVMAssociate Professor, Dairy Production Medicine
University of Georgia, College of Veterinary Medicine
Wanted: Healthy Fresh Cows, High Milk Production, Excellent Reproduction
Excellent reproductionHigh pregnancy rateCost efficient approach Reduced reproductive culls
Starts with efficient submission of healthy cows to first serviceHeat detection intensitySynchronization/ TAI protocolCompliance to TAI protocolCyclicity/ uterine health issues
EGRAPH – First Bred Event
GRAPH DIMFB
PCT DIMFB=55-85 FOR DIMFB>0 MOFSH>0 FDAT=-400 - -86 RC>1 BY MOFSH
MOFSH PCT Count Total 95% CI--------------- --- ----- ----- ------
Apr 96 52 54 87-99May 90 88 98 82-94Jun 94 77 82 87-97Jul 87 97 112 79-92Aug 94 95 101 88-97Sep 98 91 93 92-99Oct 96 94 98 90-98Nov 97 94 97 91-99Dec 96 105 109 91-99
=============== === ===== ===== ======94 793 844 92-95
21 day Preg Rate – Georgia Herd
Previously, PR ~ 14%Currently (and for the
last 2-3 years), PR = 23%
How did they make the large improvement?
GRAPH DIMFB FOR RC>1
EGRAPH – First Bred Event
BREDSUM\XN BY MYFSH FOR FDAT>-400
Conception risk by DIM and by Month/Yr of Calving
Herd’s VWP = 70 d98% of cows serviced
in first cycle
Reproductive Performance (i.e., High Pregnancy Rate & Conception Risk, Low Reproductive Culls)
Dry Cow MgmtNutritionHousing“Stress”
Energy Balance/Feed Intake
(Somatotropic axis, Ketosis, NEFA, BHBA
Issues)
CyclicityUterine Health
(Metritis, Endometritis)
Semen IssuesQualityHandlingTimingHealth
Sexed Semen
Insemination Issues Intensity/ Accuracy
Heat DetectionTAI Protocol
TAI Compliance
Immunocompetence(Neutrophil function, antibody
production, antioxidant status)
“Bull” Factors“Cow” Factors
Endometritis: Largest Impact on Reproductive Performance of Uterine Dz Issues
Clinical endometritis Muco-purulent to purulent
vaginal discharge after ~ 28 DIM
~ 20% of cows affected Often ~ 30 day increase in
median days open Reduction in FSCR Reduction in PR
Subclinical endometritis Presence of inflammation in
the uterus but without clinical signs
Usually between 35 – 75 DIM May affect 10 – 50% of cows Typically, ~ 30 day increase
in median days open (29 – 88) and reduction in FSCR
(LeBlanc et al., 2002; Kasimanickam et al., 2004; Gilbert et al., 2005; Kasimanickam et al., 2004, 2005; Hammon et al., 2005; Galvao et al., 2007, Dubuc et al., 2009)
Impact of Clinical Endometritis on Repro
LeBlanc et al, 2002
0 90 180 270 360 450
0.00
0.25
0.50
0.75
1.00
SC Endometritis (8 wks) vs. Days to Preg
Pro
porti
on O
pen
Days In Milk
123 Days
157 Days
P < 0.001
Impact of SC Endometritis on Repro
SC endometritis negative (n=152)
SC endometritis positive (n=138)
Doug Hammon; Utah State University
Treatment of Clinical Endometritis:Intrauterine Infusions or Prostaglandin?
Prostaglandins
10 – 30 DIM: No benefit at 14-28 DIM
(Glanville and Dobson, 1991, Morton et al.,1992) No benefit in normal cows at 25 DIM
(Gay and Upham, 1994) Better CR in 1st lact cows tx at 12 DIM
(Melendez et al 2004)
> 30 DIM: More cost effective than palp/ tx
approach (Pankowski et al., 1995) Improves HDR (and +/- on CR) Good lead into a TAI program
Infusions
10 – 30 DIM: Oxytet/ Pen/ Iodine: No repro benefits
(Nielson, 1979, Thurmond et al., 1993, Brooks, 2000, Heuwieser, et al 2000)
Which cows to treat?
> 30 DIM: Antibiotic infusion
(Knutti, et al 2000, LeBlanc et al., 2002) Improvement in repro performance Better choice in severe cases (?)
Choice depends upon preferred method of fresh cow management and treatment options available
Treatment of SC Endometritis Variable results of treatmentGalvao et al., 2009:
PGF at 21, 35, & 49 DIMImproved FSCR overallNo impact on % with SCENo impact of fertility of cows
with SCEDubuc et al., 2010
PGF at 35 & 49 DIMNo impact on % with SCENo impact on FSCR or median
time to pregnancy
Kasimanickam et al., 2005:PGF or IU cephapirin at 20-33
DIM improved PR (HR = 1.7 and 1.89, respectively)
Metritis: Flacid uterus containing fetid fluids (fever +/-), 2-10 DIM
Metritis IncidenceWidely variation in
reported incidence2.2 – 37 % w/ median
10.1% (Kelton, 1998)Commonly thought to
affect 10-20% of dairy cowsMarkusfeld, 1997 – 21%Hammon, 2006 – 22 %Huzzey, 2007 – 25%
Common Risk FactorsHypocalcemiaStillbirthDystociaRetained Fetal
Membranes (Emanuelson et al., 1993, Erb
et al., 1985, Gröhn et al., 1989, Kaneene and Miller, 1994, Markusfeld, 1984, 1987)
Metritis and Repro Meta analysis (70 papers) by Fourichon, 2000
Prolonged days to first service (7) Reduced FSCR (20% lower) Increase in days open (19)
Overton and Fetrow, 2008 Increased median days open (33) 3 – 4 pt reduction in PR
Frustration comes from inability to normalize repro following aggressive treatment
Dubuc et al., 2010 Decrease in first service conception risk (35.5 vs. 27.2 P=0.02) when
examining univariate outcomesWhen adjusted for endometritis, parity, and level of milk
production, no effect on first service conception risk or time to pregnancy
Smith et al., 2010 – Fresh cow douching project Enrolled ~ 3000 cows and randomly treated half the cows in
a large western dairy Tx: 30 cc of 1% Povidone iodine in 2 L of warm hypertonic saline
Postpartum uterine douching had no effect on metritis risk
Risk factors associated with metritis: RP, dystocia, parity (1st lact), twins
What About Prophylactic Fresh Cow Treatment to Affect Metritis Risk?
No (%) Yes (%) P‐valueDouche No 1278 (84.9) 227 (15.1) 0.95
Douche Yes 1276 (84.9) 228 (15.1)
Metritis
Take Home Re: Uterine Health Treatment and Reproductive Performance
Prevention is far better than treatment Often unable to restore normal fertility following metritis,
endometritis, subclinical endometritis In my opinion, best approach is still Presynch series with 2 doses of
PGF 14 days apart starting at > 30 DIM
We should be focusing on improving immunocompetence and energy balance to improve early reproductive performance Negative energy balance indicators (NEFA’s prepartum and BHBA’s
postpartum) are associated with risk of RP, uterine disease, and impaired reproductive performance
(Duffield, 1997; LeBlanc et al., 2004 & 2005; Duffield et al., 2009: Ospina et al., 2010; Dubuc et al., 2010)
Review – Energy Challenges
Adapted from Leroy et al., Reprod Dom Anim 43 (Suppl. 2), 96–103 (2008)
Nutrient Prioritization:Genetically programmed to spare glucose peripherally to support
milk production
Metabolic Adaptations for CatabolismNEB, BCS lossLow insulin, low IGF-1, low leptinHigh GHHigh NEFA, high ketonesLow glucosePeripheral insulin resistance
FertilityHypoth-pit-ovarian-axis
Oocyte/ corpus luteum qualityEmbryo quality
Increased Susceptibility:Metabolic diseaseInfectious disease
Changes in DMI, NEFA, and BHBA “Upstream” Can Have Negative Consequences “Downstream”
(Blue = Normal Red = SCE)
-2 -1 1 2 3 4 58.00
11.60
15.20
18.80
22.40
26.00
Dry
Mat
ter I
ntak
e (k
g/d)
*
*
*
**
*
A
-2 -1 1 2 3 4 50.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
NEF
A (m
Eq/L
)
*
*
*
*
**
B
-2 -1 1 2 3 4 5Weeks Relative to Calving
500
760
1020
1280
1540
1800
BH
BA
(um
ol/L
)
**
**
C
Hammon, 2005
DMI and Metritis
0
4
8
12
16
20
-13 -10 -7 -4 -1 2 5 8 11 14 17 20
Healthy
Mildly Metritic
Severely Metritic
Cows with more severe clinical
infection
DM
I (k
g/d)
Day from CalvingHuzzey et al. 2007, J. Dairy Sci. 90: 3220-3233
Odds of severe metritis increased by 2.87 for every 1-kg decrease in DMI during the close up period.
Postpartum Energy BalanceHigh milk production does not “cause” more NEBPostpartum energy balance more closely related to
energy intake (i.e., dry matter intake) than energy output (i.e., fat corrected milk production)
Minimizing negative energy balance (impact and duration) is most likely to be accomplished via successful feeding & management vs. decreasing milk yield
(Grummer et al., 2003, 2008)
Practical and Timely Monitoring:Need to Focus More on Processes, not Merely
Outcomes Goals - target levels of performance Outcome – resulting performance Metrics - any type of measurement that may be used to gauge
performance, i.e., is the herd meeting its goals. The best metrics represent some component of the process and are
always important in achieving a goal, but are not synonymous with the goal themselves
Ex: average age-at-calving for replacement heifers If the average AGEFR = 27 months, it might be a good goal to lower this age by
a few months AGEFR is an appropriate goal (and outcome), but a horrible monitor It is the result of many processes including feeding, housing, vaccination,
breeding, etc.
Key Monitors: Fresh Cows
Feed intakeStocking densityCow comfort/ standing times
Clinical disease and health issuesEnergy status monitoringBHBA’s – during week 1 or 2Fat:Protein ratio
Milk production
Critical Metrics for Nutrition and Feed Delivery
Pen counts/ stocking density/ bunk space/ resting area
DMI
Feed dry matter (are you feeding what you think you’re feeding?)
Energy density of the rationUrine pH’s – weekly basis on close-up cowsGoal – all cows 6.0 to 6.9 (Don’t care about the “average”)
Close-ups (-21 to Calving)
Fresh Cows (2 to 21 DIM)
1st Lactation > 24 lbs > 34 lbsMature Cows > 27 lbs > 42 lbs
What has been the Pattern of Calvings Over Time?
Are there large swings in the number of animals calving? Large swings can wreak havoc on even the best transition
programs due to Overcrowding the housing facilities or Overwhelming management’s ability to properly monitor and treat
fresh cow problems
Swings may result from Purchase of large groups of replacements Inconsistent reproductive management Seasonal breeding challenges (heat stress)
Calving history for past year• 1350 cows milking• 132 calvings/ mo• 31 calvings/ wk
• min = 13• max = 61
• If in close-up pen for 3 weeks, avg 93 cows predicted (std dev = 22)• ~ 46% of cohorts
overcrowded• ~ 28% of the time,
overcrowded by 10+%
Egraph
Planning Ahead: What is the Anticipated Number of Calvings for the Future?
SUM BY %118.DUE.7.WKDUE LGRP FOR CDAT>0 CDAT>-280\G
Grouping and Pen Movement Suggestions:Strive to provide ~ 30” of bunk space per animal in
close-up and fresh pensWatch out for seasonal changes in calving patternsAnalysis of herd calving patterns (Ca, Co, NC, & Ga)
Allowed Bunk Space (% of Avg # Calving)
Avg % Overcrowded
100% 48%110% 33%120% 26%130% 16%140% 9%150% 4%
Beta-HydroxyButyric Acid (BHBA)Good predictor of negative energy balance postpartum BHBA = 1000 – 1400 µmol/L – subclinical ketosis BHBA > 1400 µmol/L – clinical ketosisWeek 1 cutpoint - BHBA > 1000 – 1200* µmol/LOptimum for predicting likelihood of DA, metritisStrong association with subsequent clinical ketosis and
decreased milk production
Week 2 cutpoint - BHBA > 1400 µmol/LGreatest association with decreased milk yield
(Duffield, 1997; LeBlanc et al., 2005; Duffield et al., 2009)
What Fresh Cow Disease Issues Are Actually Being Recorded In A Consistent Manner?
Herds often have good intentions, but fall short in their efforts
Issues:Failure to record themFail to enter them in computerInconsistent definition across workersInconsistent efforts to diagnose problems
i.e., detection bias – ex. ketosis
Do The Patterns Of Fresh Cow Disease Indicate Any Problem That Needs Further Investigation?
Sample Fresh Cow Data from a Western HerdEvent Total 8-Jan 8-Feb 8-Mar 8-Apr 8-May 8-Jun 7-Jul 7-Aug 7-Sep 7-Oct 7-Nov 7-Dec
FRESH 763 73 64 60 53 48 60 73 61 54 80 71 66
DA 37 1 2 3 2 2 4 5 7 5 3 2 15% 1% 3% 5% 4% 4% 7% 7% 11% 9% 4% 3% 2%
MF 62 7 5 6 3 2 5 6 6 4 6 7 58% 10% 8% 10% 6% 4% 8% 8% 10% 7% 8% 10% 8%
RP 53 5 3 2 4 3 3 5 4 7 6 8 37% 7% 5% 3% 8% 6% 5% 7% 7% 13% 8% 11% 5%
Other questions to ask:Is there a difference in fresh cow disease risk by parity?What about stillbirths/ dystocia risk by parity
< 4%
< 4%
< 8%
Events\5si for lact>0
What Has Been The Level Of Stillbirths and Dystocia For Each Lactation Group?
EVENTS\3SI BY LCTGP
Commonly stated goals: 1st lactation: < 10-12%Mature cows: < 6%Blended: < 8%
How is Early Lactation Production Across Time?
Does early lactation performance indicate any problems with individuals, specific groups, or season?First official test day milk
Week-4 milk (must create this item – item type 122)
First projected 305me estimate
SUM W4MK F305 BY MOFSH LGRP FOR W4MK>0 F305>0 LACT>0 MOFSH>0 FDAT>-365\B
SUM W4MK F305 BY LGRP MOFSH FOR W4MK>0 F305>0 LACT>0 MOFSH>0 FDAT>-365\B
What Percent Of Early Lactation Milk Weights Are Below Some Targeted Cut-point?
“Exception monitoring”A crude approach to assess how well a group of
animals has performed or to look for “exceptions”Example:Percent of first lactation cows that are less than 100
days-in-milk that are below 50 lbs of milk at test datePercent of first lactation cows that have a first test
milk below 50 lbs of milkPercent of mature cows with first test below 70 lbs
Do The 1st Test Fat Results Suggest Any Problem?
Using milk fat and protein results to assess health and performance is a controversial
Fat that is mobilized to support milk production is broken down into NEFA’s and can be utilized in a variety of ways: 1. It can be used by peripheral body tissues for energy, 2. It can go to the liver:
1. It can be oxidized (completely or incompletely- resulting in ketonebodies) or
2. Be re-esterified into fat and stored in the liver
3. It can be taken up by the mammary gland, resulting in an increased level of fat in milk.
Other Herd-Level Monitors for Transition Management:First Test Fat:Protein Ratio
Evaluate the ratio of first DHIA test butter fat (%) to protein (%) – usually restrict to ~10 – 30 DIMFTExample: cow 304: fat= 5.1%, protein =2.8% - ratio = 1.8
On the individual cow, not a very good testSe ~ 65-70%, Sp ~ 55-60%
Better test at herd level Se >80%, Sp ~ 70%Goal – < 40% of cows with 1st test F:P > 1.4 (DIMFT= 10-40 DIM)Average ~ 40% but good herds can get to 25% or less
(Duffield, 2004)
PCT RAT1>1.4 FOR RAT1>0 LACT>0 MOFSH>0 FDAT=-400 - -45 BY LGRP MOFSHMOFSH PCT Count Total 95% CI
--------------- --- ----- ----- ------Jan 8 46 598 6-10Feb 20 88 431 17-24Mar 9 45 514 7-12Apr 23 98 428 19-27May 11 59 555 8-13Jun 39 184 477 34-43Jul 20 30 151 14-27Aug 42 218 520 38-46Sep 4 17 437 2- 6Oct 23 63 272 19-29Nov 0 0 263 0- 1
=============== === ===== ===== ======LGRP=1 18 848 4646 17-19
Jan 3 7 262 1- 5Feb 9 24 259 6-13Mar 8 26 334 5-11Apr 17 35 209 12-22May 11 27 237 8-16Jun 31 66 216 25-37Jul 22 21 96 15-31Aug 26 94 356 22-31Sep 6 21 330 4-10Oct 13 50 371 10-17Nov 0 0 306 0- 1
=============== === ===== ===== ======LGRP=2 12 371 2976 11-14
MOFSH PCT Count Total 95% CI------ --- ----- ----- ------
Jan 5 58 1056 4- 7Feb 18 156 890 15-20Mar 9 95 1028 8-11Apr 23 182 778 21-26May 12 115 967 10-14Jun 38 345 903 35-41Jul 23 72 318 18-28Aug 38 450 1190 35-41Sep 5 60 1106 4- 7Oct 22 209 966 19-24
====== === ===== ===== ======19 1742 9202 18-20
Key Monitors: Close-up Pen
Stocking densityFeed intakeParticle size – Is sorting a problem?
Urine pHEnergy measuresNEFA’s prepartum
Days in close-up penHousing and comfort
Elevated NEFA’s Before Calving
Associated with:~1.5 X ↑ risk of RP (LeBlanc et al, 2004)
~2-3 X ↑ risk of subclinical ketosis (Gooijer et al, 2004)
~2.2 X ↑ risk of Met (> 0.37 mEq/L) (Ospina et al, 2010)
↑ risk of LDA: ~ 2 X (> 0.27 mEq/L) (Ospina et al, 2010)~ 4X (> 0.5 mEq/L) (LeBlanc et al, 2005)
19% ↓ risk of pregnancy within 70 days of VWP (> 0.27 mEq/L) (Ospina et al, 2010)
NEFA TestingGood estimate of excessive body fat mobilization
prepartum (before calving)Sample Population: Close-up dry cows 2 to 14 days
before calving Cutoff: > 0.3 mEq/Liter (Ospina et al, 2010)
> 0.4 mEq/Liter* (Cook et al, 2006)
> 0.5 mEq/Liter (LeBlanc et al, 2005)
Alarm level being suggested is > 10%
Grouping and Pen Movement Suggestions: *Try to avoid moving cows during last 10 days before calving
(strive for > 14 days in close-up pen)
Depending on the herd, may need to target for an avgDINCU > 23 in order to ensure most cows have adequate time in close-up
In this data set:- 64% of cows spent14 – 30 DINCU
- ~ 90% spent 10 – 40 DINCU
Key Monitors: Far Dry Cows
Feed intakeRation composition – avoid overfeeding energyTotal days dryHousing and comfort
Do The Patterns Of Previous Dry Period Length or Days In Close-up Match The Management Plan?
SUM DDRY BY MOFSH FOR FDAT>0 MOFSH>0 PDOPN=50-300 FDAT>-365
SUM DINCU BY MOFSH FOR FDAT>0 MOFSH>0 DINCU>0 FDAT>-365
By MOFSH %COW #COW Av DDRY--------- ---- ------ -------
Jan 8 66 64Feb 6 48 63Mar 6 49 64Apr 8 66 60May 8 61 65Jul 9 69 62Aug 12 95 59Sep 12 97 56Oct 10 75 55Nov 9 70 56Dec 11 82 57
========= ==== ====== =======Total 100 778 60
By MOFSH %COW #COW AvDINCU--------- ---- ------ -------
Jan 8 91 20Feb 6 65 19Mar 8 89 25Apr 7 84 23May 11 124 22Jul 7 76 21Aug 11 127 26Sep 13 141 23Oct 10 110 22Nov 10 108 19Dec 10 108 18
========= ==== ====== =======Total 100 1123 22
Should also examine frequency histogram to look at the variation for each of these measures (Graph DDRY or Graph DINCU)
Be Careful with Long Days Dry
Rollin et al., 2010 – Clinical trial with CatosalCows with long days dry (> 70):Increased odds of elevated BHBA postpartum(adjusted for tx, RP, farm, and BCS)
Need to rethink our management of cows with long days open and early dry-off
Reproductive Performance (i.e., High Pregnancy Rate & Conception Risk, Low Reproductive Culls)
Dry Cow MgmtNutritionHousing“Stress”
Energy Balance/Feed Intake
(Somatotropic axis, Ketosis, NEFA, BHBA
Issues)
CyclicityUterine Health
(Metritis, Endometritis)
SemenQualityHandlingTimingHealth
Sexed Semen
Insemination Intensity/ Accuracy
Heat DetectionTAI Protocol
TAI Compliance
Immunocompetence(Neutrophil function, antibody
production, antioxidant status)
“Bull” Factors“Cow” Factors
