To cull or to keep? Often, it’s not so straightforward.
Dairy producers are faced with many deciding factors when selecting replacements and when culling on their operations. One sometimes gray area? Health and immunity.
The good news? Researchers across the country are working to provide data that can help producers in those decisions, says Kent Weigel, professor and chair, Department of Dairy Science, University of Wisconsin–Madison.
“Through the years, selection within dairy herds has evolved from high production and functionality to visual appraisals,” Weigel says. “Then, selection moved to somatic cell score and mastitis resistance in the early 1990s. Now, it has continued to evolve to include stillbirths and zeroing in on various, specific problems.”
Across-herd genetic information for health and immunity is still a work in progress. One of the main reasons: On-farm records of health issues, such as mastitis and lameness, can vary from one farm to the next, Weigel says.
“What I call ‘lame,’ and what you call ‘lame’ could be different, for example,” he says. “We can’t look at the data and say one farm is doing better with one trait than another—as one may not be properly diagnosing or recording issues.”
However, Weigel says, contemporary comparisons across numerous operations can even the heritability estimations.
“Daughters of Bull A, compared to Bull B and Bull C, can be evenly evaluated even when records aren’t kept consistently among herds,” Weigel says. “Producers who diagnose more aggressively will diagnose more aggressively across the board. And producers who diagnose less aggressively will diagnose less aggressively across the board. The data does even out, and we will know when certain sire families have higher incidences.”
This was the principle that helped to launch a bull list with genomic predictions, based on on-farm wellness records, for wellness traits last year.
“From this information, we could see the very best and very worst on what happened within certain sire families in first and second lactations,” Weigel says. “Was it revolutionary? Not really, in the sense we already had general ways to measure health and wellness within herds. But this allowed us to be more precise and accurate with our information.”
Research at the University of Guelph has found that 25% of the differences between animals for immune response can be attributed to genetics.
“This study got beyond the issues of hygiene in milking procedures, which varies greatly from farm to farm, and got closer to measuring the health of the cow in its methodology,” he says. “It’s naive to say there is one simple test to say one bull is good and one is bad. But if you have reasonable expectations, with everything else being equal, you could have a chance of knowing that one bull might have a better chance than another at producing healthy offspring.”
So what does this mean for your operation? Eventually, Weigel says, genomic data could help you select for stronger resistance to health issues sometimes missed in on-farm evaluations.
For example, he says, clinical diagnosis of ketosis is low. Studies are being conducted, however, measuring cows more aggressively for the condition.
“We are measuring cows at the University of Wisconsin–Madison four times, from five to 18 days post-calving, to determine the peak in blood BHB (beta hydroxybutyrate),” Weigel says. “If we can put that into genetic evaluation, we could have something valuable. If you’re only checking one day, you could miss it because of timing.”
Weigel says it’s not practical to measure all cows this often. However, genetic predictions could compare potentially tens of thousands of cows, offering producers information they can use in genetic selection.
Studies are also being done on calf respiratory disease.
“You can go out and check calves for coughs and runny noses, or we can ultrasound those calves at three and six weeks of age to check for lung lesions,” Weigel says. “It’s not something you can do on every calf on your own operation, but it’s very accurate. Hopefully, though, we can go to large operations soon and ultrasound hundreds or thousands of calves to gather genomic data.”
Producers and researchers will continually learn more about the ties between genetics and health as more data from automated recording systems become available, Weigel says. These systems remove much of the recording variation out of the data, giving a more consistent view of disease incidence.
“Ultimately, we are probably not looking at a single measure, but a collection of data points that will give dairy producers and their management teams a more complete picture of how health and genetics go hand in hand, leading to more healthy and productive cows,” he says.
Incredible advancements have been made in predictions on production, body size, fertility and mastitis resistance, Weigel says. Never forget, however, that common sense can also be a useful tool.
“You can learn a great deal simply by sifting through your dairy-herd-management software data and seeing which cows get recorded the most often,” Weigel says. “Those invisible cows—the ones the farmer hasn’t seen in the sick pen and who are just doing their jobs—are often the most valuable to an operation.”