But a lot has changed in the 90 years since the national judging contest began. These days, farmers use more than their eyes to tell them about a cow’s milk-making potential. They rely on extensive data about her pedigree and the performance of her mother and aunts and sisters. And now the sequencing of the cow genome—completed in 2009 by a team of 300 scientists from 25 countries—has opened a vault of new data and new possibilities.
That was demonstrated during one of Expo’s biggest events, the Friday night Holstein sale, when auctioneer Tom Morris brought down his gavel to sell a four-month-old calf for $87,000, the highest price paid all week. Two weeks before the auction, that calf had topped a ranking of Holstein heifers by Genetic Total Performance Index, a prediction of her future performance gleaned by scanning her chromosomes for the presence of certain genetic markers. Although the calf came from a long line of top performers, her outstanding genetic report card undoubtedly helped fuel the bidding.
When the University of Wisconsin proposed to set up a genetics department in 1910, it had the enthusiastic backing of W.D. Hoard. But he wanted a different name. “Genetics,” he said, was a technical term that the state’s dairy farmers wouldn’t understand.
It didn’t take them long to catch on. Through genetic selection, the dairy industry has been able to achieve astounding gains in the quality and quantity of milk that cows make. Since 1939, the nation’s dairy herd has shrunk by 60 percent, but it produces 20 percent more milk because the average cow’s production has more than quadrupled.
Those increases were accomplished through the development of a gene pool that is not only deep, but also extremely well cataloged. In the 1800s, breed associations began keeping herd books to record the pedigrees of high-performing animals. Soon after, the emergence of the Dairy Herd Improvement record system created a standardized way to compare various bulls and cows by keeping track of how much milk their offspring produced. Today the industry collects data on well over half of the nation’s nine million dairy cattle, recording not just milk yield, fat and protein, but also data related to things like health, fertility and milk quality. International producers have adopted the same framework, creating a vast database of cow performance that spans the globe.
For Kent Weigel, a CALS dairy scientist whose work focuses on genetic selection, the records offer a trove of data that can be mined to optimize breeding. “We can statistically analyze those data and figure out which are the best families to select as parents of the next generation,” he says. Currently, the way most breeding companies do that is to collect and sift data on the progeny of their breeding bulls. It’s dependable, says Weigel, but slow. “It’s at least five years before you get any information and can decide if it’s a good bull you want to keep or a bad bull that you want to get rid of.”