The same for less: Genetic science holds the key to better feed efficiency in dairy cattle
As the eighth largest dairy-producing state in the country*, Michigan is home to more than 400,000 dairy cows spread across farms with herds numbering less than 100 up to thousands. Feeding such a large number of animals is a challenging task. With each animal eating approximately $5 in feed every day, Michigan dairy farmers spend over $730 million each year to keep their herds well-nourished and to produce enough milk to meet consumer demand.
Michael VandeHaar, Michigan State University (MSU) AgBioResearch livestock nutritionist, and his colleagues are working to bring that cost down by combining genomics and nutrition science to breed cows that require less food to produce the same volume of milk.
Following the discoveries made by the Human Genome Project, which hadnumerous implications for animal science, livestock breeders have begun taking advantage of the wealth of dairy cow genetic information to select bulls capable of passing along to their progeny desirable traits such as size, milk production and disease resistance. Being able to genetically select bulls for feed efficiency, however, has been comparatively more difficult. Because cows on commercial dairy farms are fed in groups, acquiring data on how much an individual animal consumes has been nearly impossible.
“Genomics will now allow us to do just that,” said VandeHaar, professor of dairy nutrition and metabolism in the MSU Department of Animal Science. “We can study the DNA of cows in university dairy herds and look for genetic markers for feed efficiency and deliver that information to the industry.”
In 2010, VandeHaar and fellow MSU AgBioResearch scientist Rob Tempelman — with research partners at the University of Wisconsin-Madison, Iowa State University, the University of Florida, Virginia Tech and Wageningen University in the Netherlands — were awarded a $5 million grant from the U.S. Department of Agriculture (USDA) National Institute of Food and Agriculture to find genetic markers for feed efficiency. Five years later, as the project nears conclusion, success is well within their grasp.
VandeHaar and his colleagues collected feed intake data from 7,000 cows from university herds in Michigan, Wisconsin, Iowa, Florida, Maryland, Virginia, New York, Alberta, Scotland and the Netherlands. The team identified which animals ate less than expected, on the basis of their production, and took genetic samples for analysis. Most samples were analyzed by industry partner GeneSeek (a subsidiary of the Lansing-based Neogen Corporation), and the data were submitted to the USDA Animal Improvement Laboratory in Beltsville, Maryland, where much of the genomic data on the U.S. dairy herd is kept. The lab staff processes the samples and sends VandeHaar and Tempelman the list of individual elements, called single-nucleotide polymorphisms (SNPs), that make up each animal’s genome. The team can then analyze those SNPs through statistical modeling to determine which are related to feed efficiency.
The team has genotyped 5,000 of the cows so far and is currently analyzing the remaining animals, as well as collecting feed intake data on 1,000 more cows. Once the process is complete, they will have a final equation for feed efficiency that they can pass on to the industry.
VandeHaar’s colleagues in Wisconsin are developing extension and educational tools to communicate their findings to breeders, producers and dairy nutritionists. In addition to communicating the new information uncovered on cow genetics, the team’s extension plans also include providing the industry with a state-ofthe- art web-based tool to analyze feed efficiency and grouping practices on commercial farms.
The results of their combined efforts will reduce feed costs without sacrificing production.
“Though it’s difficult to put a dollar figure on it at this point, we have seen results from an Australian team that did a similar project,” VandeHaar said. “We think it is reasonable that we could reduce feed costs by 50 cents per cow per day, which, if you can do that for all the cows on a farm for a year, adds up to some pretty significant savings.”
Though the numerous other traits used by breeders to select bulls will continue to be important, VandeHaar and his team are adding one more tool to their toolbox.
“Breeders must still select for the cows that produce the most milk — that’s not going away,” VandeHaar said. “We’re adding an additional trait that can help them select for the most efficient cows — cows that will reduce their feed costs.”
VandeHaar predicts that their results will be ready for industry-wide implementation within two years.
“The day is coming when the genetic values for feed efficiency we found will be included in the bull selection process,” he said. “That is going to make a difference in the dairy industry, and to know our group was a part of that is incredibly fulfilling.”
*According to the USDA National Agricultural Statistics Service.
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