Tools for Making Economic Culling Decisions

A recent USDA Cattle Inventory Report identified that Pennsylvania was down 5,000 head of milk cows at the start of 2014 compared to 2013 (NASS, 2013). Dairy replacement heifers 500+ pounds for Pennsylvania were up 5,000 head, suggesting there are ample replacements for Pennsylvania dairies in 2014. Considering cull prices should remain steady due to lower beef inventories currently in the U.S., greater culling decisions could be made on dairy operations this year. To assist with those tough decisions, there are a few test-day metrics that can help sort out the top and bottom of the average cull list.

Economic vs. Biological Culls

In order to make the most of culls, cows need to leave the herd based on low production or dairy purposes. Fetrow et al. suggested in a 2006 culling nomenclature review that these low production or dairy purpose culls be considered "economic" culls, instead of the more popular "voluntary" culls. Other culls, those typically labeled "involuntary," should be considered "biological" culls. For herds to have success with culling strategies, accurate data is crucial to determining why animals have left the herd. If all culls fall into the biological cull category, the producer's decision to cull is nearly made for them. Cows in the economic cull category allow for greater producer control over which animals stay or leave.

Potential Production Metrics

Making economic culls on current test day production alone may not be enough under current market changes. Variables like lactation to date (LTD) milk and projected 305-d mature equivalent (ME) milk can aid in ranking cows based on overall lactation performance. Potential metrics like Dairy Comp 305 current relative value (RELV) or PCDart Money Corrected Milk™ (MCM) can also enhance the ranking of cows on overall performance. RELV is based on ME305 and is an average of the herd ME. So cows less than 100 are lower than herd average, and those above 100 are higher than herd average. MCM™ is a relatively new metric to PCDart. The variable is a measure of cow productivity based on market values (either component or fluid market) and other milk check values for a specific herd. This allows the calculated value to be based on market value of milk, not just the energy of milk.

A Ten Cow Example

To best demonstrate how different metrics can be used to sort out potential culls based on production, ten cows from a sample farm were selected. Cows were selected based on their reproductive diagnosis of open or do not breed, or based on DIM > 250 and days until due > 100. Cows with current production greater than the herd average (in this case, 80 lbs on the most recent test) were excluded. The resulting ten cows are listed in Tables 1 and 2. Table 1 depicts the current test day production values for the 10 cows, while Table 2 presents some of their current lactation and ME 305D measurements. Just looking at individual values may not clearly show which cow should be culled.

¹Confirmed Pregnant
²Confirmed Do Not Breed
³Confirmed Open

These cows were then ranked by three current test day production metrics and by five current lactation metrics, as seen in Chart 1. Within the three current test day metrics, cows at the top of the list and bottom of the list were consistently ranked. There was a little bit of change for cows in the middle ranking area. In lactation ranks, cows again remained at similar ranks in the top and bottom, regardless of the metric used. The changes occurred again within the middle ranking area. It is important to note there were some large rank changes when comparing current test day to current lactation. This demonstrates the importance of considering both current performance and overall lactation performance when trying to determine which cows may be culled for economic reasons.

Chart 1. Cow Rankings on Individual Production Metrics

Summary

Greater heifer inventories and strong beef prices can put greater pressure on the decisions to cull an animal. For herds to be successful with their culling strategies, greater control over decisions via economic culls is a must. Making those economic culls based on accurate production data (that considers components and current markets) is another critical component. Finally, examining performance for both current test day and overall lactation will enhance the information available to make the final decision.

References

• Fetrow et al., 2006. Invited Review: Culling: nomenclature, definitions, and recommendations. Journal of Dairy Science, 89:1896-1905.
• USDA, Cattle (January 2014). National Agricultural Statistics Service. January 31, 2014. Accessed 2/2/2014.