I was a dairy farmer before synch programs, sexed semen, and using beef semen to manage heifer inventory. In those days it was not unusual to run short of replacements and buy cows to maintain herd size. I bought replacements from the best herds in the area, but they were never the best cows in my herd. My cows were not better than anyone else’s, but they had generations of selection to be better adapted to my management than anyone else’s. That’s genetic improvement through culling.
There are some good tools out there to select the right bulls for your robot herd, but what about tools to select the right cows to stay in your robot herd. Recently I helped a customer develop a simple cow index to combine robot performance with production traits. All of the information we used came from Horizon.
The production component
We based production information on predicted 305-day production, and average fat and protein. I used Excel to calculate expected 305-day combined fat and protein. If those values were not available, we could have substituted total milk in the first 50 days of lactation, peak milk, or DHI values. 305-day combined fat and protein was multiplied by a factor to provide the weight we wanted in our selection. Our predicted 305-day values were not age adjusted so we applied our index within lactation groups but not across lactation groups. We could have assigned different factors to different lactation groups to allow comparison across lactation groups.
The robot performance component
The robot performance component of the index included cow behavior and robot performance. Our cow behavior metric needed to measure the cow’s willingness to come to the robot. Milkings are not the ideal measure because there is no way to tell whether a milking is voluntary or fetched. We chose refusals instead, because almost all refusals are voluntary. Gate passages would work just as well in a guided flow barn. We used milk yield per box time to measure how efficiently the cow uses her time in the robot. Again, a factor was applied to each of these values to weight them for the farm’s management goals.
Putting them together
When all the calculations were completed in Excel, the average first lactation cow had a fat and protein index of 312, a refusals index of 32, a yield/box time index of 85, and a total index of 428. The actual values are arbitrary.73% of the value came from production, 7% from behavior, and 20% from robot performance. The factors could be adjusted to shift the importance of the traits. A smaller factor for robot performance would put more weight on production and behavior.
This index does not have the accuracy of a genomic prediction, but it does use real farm data, and it can be adjusted to reflect the farm’s priorities. The 48th cow on a list of 100 may not really be better than the 53rd cow. The top third includes the elite robot cows. They can be inseminated with sexed semen to increase the impact of their offspring. The bottom third includes the lower performing robot cows. They can confidently be culled or inseminated with beef semen.
To maximize your genetic progress, use a cow index for culling and preferred semen on the cow side, and all the sire selection information the industry provides on the bull side. Cow Corner can help you build an index from your records to reach your goals.
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