By Bob Mitchell BS’76
From computer vision to cloud computing, CALS scientists are finding ways to gather and analyze massive amounts of information for better farm management
28
grow
FALL 2019
The video clip shows some very colorful calves. It’s an overhead view of five young Holsteins, but none of them is black and white. They are either red, green, yellow, indigo, or sky blue, and they keep changing color as they move about the pen. These are six-week-old calves as seen by a computer — one that’s been trained to identify each animal by the pattern of her coat and to recognize and record what she’s doing. Each color signifies a different behavior: standing, lying down, drinking water, drinking milk, or eating. This is valuable information for a dairy farmer, says CALS dairy scientist João Dórea. A calf ’s behavior tells the farmer a lot. Just like a human child, a calf that’s beginning to get sick is lethargic and doesn’t have much appetite. A parent with two or three kids might notice these changes, but for a farmer who’s raising dozens or hundreds of calves, it’s not so easy. “It’s a tiny change that’s hard to spot,” Dórea says. “By the time the farmer notices it, it’s often too late.” A team of CALS researchers is working to change that. They’re building an automated system that uses computer vision technologies — akin to what guides Google cars and lets your photo app match faces to names — to watch calves 24 hours a day. Their system will not only warn
a farmer if a calf is getting sick but also track her growth and predict her future success as a milking cow and mother. The idea for this system was hatched on the fourth floor of the UW–Madison Animal Sciences Building in the lab of animal sciences professor Guilherme Rosa. Rosa and Dórea (who worked in Rosa’s lab until he joined the dairy science faculty in July 2019) and their students and postdocs wrangle “big data” — a term that refers to the vast volumes of complex information now being generated and streamed continuously from many sources in many forms. They use artificial intelligence, cloud computing, and sophisticated statistical tools to dig deep into mountains of farm data, searching for patterns that can help farmers better understand what is happening with their animals. These researchers work at two very different scales. Some projects zoom in on individual animals, using sensor technology to collect and analyze data in real time about each animal’s health, growth, feeding, and behavior. “We can use this information for individualized management practices — so-called precision livestock farming, similar to personalized medicine in humans,” says Rosa, who is also affiliated with the Department of Biostatistics and Medical Informatics in the UW School of Medicine and Public Health.
