Monitoring a Dairy Farm’s Performance: Specifics

Gerard Cramer, DVM DVSc

College of Veterinary Medicine, University of Minnesota

Summary

1. Monitoring and evaluation of dairy farm performance requires being able to quickly scan key parameters of different production areas to determine if further action is warranted
2. Investigation of problem areas should focus on determining who is affected and the timing/source of the problem.
3. Follow up investigations should always be done to collaborate findings.

Introduction

To facilitate the ease of routine monitoring a veterinarian should develop a systematic questioning based process that can be transferred between herds. Based on the findings of these routine monitoring parameters a more detailed investigation may be warranted. The outcome of a record evaluation should always be to confirm your findings by a more detailed investigation of the farm and data generating process to determine

Content

This content will focus on evaluating records typically found in dairy management software.  Example commands from DairyComp will be given. On dairies there are other important sources of data that also should be considered (processor reports/feed intakes etc).  The majority of parameters are useful for both evaluating a new herd or monitoring herds on a routine basis.

Key Monitoring Questions

(link to video showing how to go through these questions in Guide)

Data Integrity Checks

If a veterinarian reviews data from a herd for the first time it is important to ensure the data is of sufficient quality to draw conclusions. Once you are reviewing data on a more regular basis it might be tempting to skip steps and in some cases this might be warranted. It is important to always consider that problems with the data might be a reasonable explanation for the trends you are observing. To check data integrity the following things should be reviewed/done at a minimum:

1. Set date to last data entry date.

1. DC Command: SETDAY\E
2. Performing this step first ensures that parameters and reports reflect the appropriate time and are not based on the date of your analysis.

2. Are current lactation, historical lactation, and departed cow records available?

1. DC Command: EGRAPH EC=1 FOR LACT>0 MYFSH>-1100 BY CRTYP\FD1100

3. Are current and historical reproductive outcome records available?

1. DC Command: EGRAPH EC=5 FOR LACT>0 \W0D1100R
2. Both these 2 questions check to ensure that appropriate historical records are available and the data being analysed are not subject to selection and survival bias.

4. Are testday data present?

1. DC Command: PLOT MILK FAT PRT RAT LSC FOR LACT>0\RZD425
2. This is a check to see the frequency of milk testing and also allows you to see test day trends for milk, fat, protein production and milk quality.

5. What events are being recorded?

1. DC Command: EVENTS FOR LACT>0\5OS365
2. This check to determine what is being recorded on the farm. Unexpected events or #’s should be noted.

6. What has herdsize been?

1. DC Command: ECON\ID
2. Allows you to determine if the herd is expanding and also provides a reliable way to the average herd size and a reliable denominator for other parameters.

Herd Characteristics

Overview

7. What are the herd demographics by lactation group and breed?

1. DC Command: SUM BY BREED LGRP
2. In a new herd this will give you a sense of the type of animals in a herd.  Once you are familiar with the herd this question is not as important.

8. What is current test day milk production, fat %, protein % and SCC?

1. DC Command: SUM MILK FAT PROT% SCC DIM FOR MILK>0 TDAT=TDATH BY LGRP\BL 
2. For routine monitoring this question gives you a quick overview of a variety of parameters.

Production

9. Has there been recent decrease or improvement in overall test day milk production?

1. Targets: HO>90, JE>60
2. DC Command: PLOT MILK FOR LACT>0 BY LGRP\RD730Z
3. Quickly allows the evaluation of trends and changes in milk production

10. Are there any individuals or lactations that are not milking well?

1. DC Command: GRAPH MILK FOR MILK>0 TDAT=TDATH BY TDY LGRP \BLP4
2. Graphically allows a quick evaluation of all cows tested on test day.  Look for patterns of cows away from trends.

Milk Quality

SCC (If on DHIA test)

11. What is testday estimated bulk tank SCC?

1. Targets: <200,000
2. DC Command: ECON %ID RPRO DCC TDY PSCC5 PSCC4 PSCC3 PSCC2 PSCC1 \SC
3. Estimates what bulk tank SCC would be based on test day information. Useful to see impact of specific cows on herd average.

12. Has the percent of infected cows increased over time for the entire herd?

1. Targets: <15-20% LS>4 or SCC>200,000
2. DC Command: PLOT SCC=200 FOR LACT>0 BY SCC\RD730
3. Tracks infection pattern(based on SCC) in the herd.

13. Has the percent of high fresh, new and chronically infected  cows increased over time for the entire herd?

1. Targets: New <8%; Chronic <10%; HiFresh <15%
2. DC Command: PLOT SCC=200 FOR LACT>0 BY SCC\RYD730
3. A more detailed look at SCC infection patterns.  Chronics are based SCC > 200 on current and past test.

Clinical mastitis

14. What has been the level of recorded mastitis EVENTS over the last complete 18 month period (Gap=UserDefined; use 7 and 14)?

1. Targets: [monthly clinical mastitis rate <5% good, <2% excellent]
2. DC Command: EGRAPH EC=37:%DAYS_IN_GAP \W0 \Z     FOR EDAY>=18MON EDAY<00MON
3. Data from this is completely dependent on clinical mastitis detection and recording. The gap is the time period between when a case should be counted as a new vs a repeat of current one.

Transition Cow Disease

15. Has the incidence risk of transition cow events changed over the past year?

1. Targets: DA<3% MET<15% RP<8%
2. DC Command: EVENTS\UD31W0

1. OR EGRAPH EC=1 EC=39 EC=42  EC=38  EC=37 EC=35 EC=32 EC=41 EC=14 EC=15 FOR LACT>0 DNM<31 FRSH>=13MON FRSH<01MON\D430 \FN1Z

3. Allows for monitoring of trends the different bars indicate different estimates of uncertainty around the actual estimate. The coloured box is a 68% and the black lines are 95% levels of uncertainty.  When monthly estimates change outside of the ranges between months it indicates a potential real change as opposed to normal variation. Of note these events are tied to the months the cow freshened not the month they occured.

Lameness (or other disease)

16. Has the incidence or type of lameness changed recently?

1. Targets:SU<5% WLD<5% DD<5%, FOOTROT<1%
2. DC Command: EGRAPH EC=36\PN1W0
3. Tracks the number of new cases of each lesions. New is considered individually for each lesion and only looks at a cow’s current lactation.

Reproduction

17.  Does the actual DIM at the first inseminations match the stated VWP?

1. Targets: 50-60
2. DC Command: EGRAPH EC=5 FOR LACT>0\SN1T150 BY LGRP
3. Allow for an examination of changes in the herd’s VWP and compliance to the dairy’s first breeding protocol

18.  How efficiently are eligible cows becoming pregnant?

1. Targets: PR>25%
2. DC Command: BREDSUM\EAD525
3. This gives you data on pregnancy riks/pregnancies per AI (conception) and AI submission Risk (heat detection).  Likely one of the useful parameter to monitor.  Should be adjusted for VWP as noted above.

Culling

19. What has been the dead and sold animal patterns by month?

1. DC Command:EGRAPH EC=14 EC=15 FOR LACT>0 MYARC>-1100 \W30D1100M

20. What has been the dead and sold animal pattern by DIM?

1. Targets: <5% in first 60 days
2. DC Command: EGRAPH EC=14 EC=15 FOR LACT>0 MYARC>-1100 \IW30D365M
3. Monitoring culling suffers from a lot of lag and should be done with care. It can be useful in herds with poor disease recording records as deaths and sold are usually entered. Determining the timing of culling allows for a determination of whetever the culls are related to transition or reproductive problems.

Replacements

21. What has been the level of calf death loss at birth?

1. Targets: < 6%
2. DC Command: EVENTS\3
3. This table is all based on data entered when a cow calves and can give you a sense of stillbirths and sexed semen use.

22. Has death rate for calves <42 days old changed (by month of birth)?

1. Targets: < 5%
2. DC Command: EGRAPH EC=1 EC=14 EC=15 \YFN1D400C FOR DNM<43 MYBDT>-400 LACT=0 RC<>8 GNDR="F" BIRTH>14MON
3. Useful in herds that do not enter calf disease events.

23. Has the number or 68%CI of animals with first scours and pneumonia by 42 days old changed (by month of birth)?

1. Targets: Scours<25% pneumonia <10%
2. DC Command: EGRAPH EC=1 EC=33 EC=41 \YFN1D400C FOR DNM<43 MYBDT>-400 LACT=0 RC<>8 GNDR="F" BIRTH>14MON
3. Very few herd enter this information but if it exist is a great monitor of calf health

24. What age are the heifers becoming pregnant?

1. Targets: <14-15 months
2. DC Command: EGRAPH EC=5 \YASR

25. Do we start breeding heifers early enough?  

1. Targets: >365-430
2. DC Command: EGRAPH EC=5 \YASR

26. What has been the heifer AI pregnancy & insemination risks?

1. Targets: PR>30%
2. DC Command:BREDSUM\EY
3. These 3 parameters should be evaluated together to determine the efficiency of a dairy’s reproductive program.

Follow up Questions

Typically a quick herd scan identifies several problem areas. Once identified further questions should be posed of the data to help determine if further action is warranted. Typically the first question that should be asked if a problem is identified is who is affected. As an example if milk production is lower than expected a follow up question would be:  Are all lactations down in milk production?  Another followup question is to determine if certain production groups/pens or reproductive categories are affected differently. A few examples of follow questions could be: Are there specific days in milk periods that milk production is below expectation? or Are there specific pens that are performing below expectation?  Once these questions have been answered more detailed examination of potential causes can be evaluated in the records or on the farm.  For example a follow question in the records could be: Do fresh first lactation animals are not milking as well do they have more transition cow diseases?

        It is easy to get caught up evaluating records and refining your questions however it needs to be remembered that typically sample size for each question becomes smaller resulting in more uncertainty about the impact of your findings.

Additional Resources

• Overton, M.W. 2011. Dairy Records Analysis and Evaluation of Performance. C.A. Risco and P.M. Retamal, ed. Blackwell Publishing Ltd., Oxford, UK. (Google drive link to chapter)

Acknowledgments