University of Florida scientists want to assess livestock mobility faster and more accurately, contributing to the health and production of livestock. To do this, they will use artificial intelligence to analyze high-definition video of the animals as they move.
Samantha Brooks, a geneticist at the University of Florida’s Institute of Food and Agricultural Sciences and an associate professor of equine physiology — along with other UF researchers — received a $49,713 grant from the Initiative du agricultural genome to phenome for this research.
The team will combine machine learning with gait analytics to speed up their assessment of livestock mobility. Brooks cites an example of how this technology can help: In horses, a veterinarian can do a basic lameness exam in about 15 minutes.
“Our long-term goal is to build an automated pipeline that could produce results in near real-time, just seconds after the animal passes the camera,” Brooks said. “This pilot project is a first step towards that goal.”
Brooks and his colleagues primarily work with horses because they are an excellent model of locomotion and because scientists can collect lots of data quickly.
She and her lab are already working with around 2,000 video clips of horses in motion. Brooks credits the hard work of graduate student Madelyn Smythe and the generosity of hundreds of Central Florida horse owners for the video.
“The large video library will allow the construction of accurate models to track animal movement in the video image,” Brooks said. “Although we started with the horse, what we learn here will translate to similar patterns for other four-legged farm animals.”
For this project, they will also build AI models to analyze videos of cattle, pigs and small ruminants.
In reviewing the data, researchers will look at horse traits such as stance time, stride length, and limb extension. In cattle and pigs, scientists are more interested in asymmetry and postures that indicate pain for abnormal functioning of one or more limbs.
Brooks says she wants to help other scientists and farm animal owners because AI, while helpful, isn’t always intuitive.
“Artificial intelligence approaches can accelerate our ability to measure complex locomotor traits in livestock, with better precision than the human eye,” says Brooks. “Yet, AI tools are often not suitable for biologists, nor ready for challenging on-farm applications. To address these issues, we hope to adapt and assemble existing AI methodologies into an analytical set accessible to scientists from diverse backgrounds and deployable in a variety of livestock management contexts.”
For example, the technology could detect lameness in cattle as they pass a camera each day. Imagine dairy cows entering the milking parlour, for example, alerting the farmer to potentially serious health issues early on and with less effort from farm staff.
Funded by the USDA National Food and Agriculture Institute, AG2PI is a three-year project ending in 2023. AG2PI’s goal is to connect crop and livestock scientists among themselves and to those working in data science, statistics, engineering and social sciences. to identify common problems and collaborate on solutions.
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