UFL/IFAS uses artificial intelligence to assess livestock mobility

Scientists at the University of Florida want to assess livestock mobility more quickly and accurately, ultimately benefiting the health and production of farm animals. 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, has been awarded a $49,713 grant from the Agricultural Genome to Phenome Initiative for this research.

The team will combine machine learning with gait analytics to accelerate their assessment of livestock mobility. Brooks gives an example of how this technology can help: In horses, one vet can do a basic examination of lameness in about 15 minutes.

“Our long-term goal is to build an automated pipeline that can provide near-real-time results just seconds after the animal passes the camera,” Brooks says. “This pilot project is a first step towards that goal.”

Brooks and her colleagues mainly work with horses because they are an excellent model for locomotion and because scientists can quickly collect a lot of data.

She and her lab are already working with some 2,000 video clips of horses in motion. Brooks thanks the hard work of graduate student Madelyn Smythe and the generosity of hundreds of horse owners in central Florida for the video.

“The large video library allows accurate models to be created to track the movements of the animals in the video frame,” Brooks says. “While we started with the horse, what we’re learning here will translate to similar models for other four-legged farm animals.”

For this project, they will also build AI models to analyze videos of cattle, pigs and small ruminants.

As they review the data, researchers will look at equine characteristics such as standing time, stride length and limb extension. In cattle and pigs, scientists are more interested in asymmetry and postures that indicate pain for abnormal function in 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 could accelerate our ability to measure complex locomotor traits in livestock, with greater accuracy than the human eye,” Brooks said. “Yet AI tools are often neither biologist-friendly nor ready for challenging farm applications. To address these challenges, we hope to adapt and merge existing AI methodologies into an analytics package that is accessible to scientists with different backgrounds and deployable in different livestock management environments.”

For example, the technology could detect lameness in livestock that pass a camera every day. Imagine dairy cattle entering the parlor, alerting the farmer to potentially serious health problems early on, and with less effort from farm staff.

Funded by the USDA’s National Institute of Food and Agriculture, AG2PI is a three-year project ending in 2023. The goal of AG2PI is to bring crop and livestock scientists together and with those working in data science, statistics, engineering, and social connecting sciences. to identify shared problems and collaborate on solutions.

Source: University of Florida’s Institute of Food and Agricultural Sciences, which is solely responsible for and fully owns the information provided. Informa Business Media and any of its subsidiaries are not responsible for the content of this information resource.

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