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Using artificial intelligence to track animal welfare

Researchers are looking to artificial intelligence to track and improve animal welfare.

The Western College of Veterinary Medicine and the University of Saskatchewan’s Department of Computer Engineering are developing new tools to document and analyze animal-based indicators of on farm welfare, such as skin or tail lesions detected on swine carcasses at slaughter.

There are also 14 industry partners involved with support from the Natural Sciences and Engineering Research Council.

Dr. Martyna Lagoda, post-doctoral fellow on Swine Behavior and Welfare, said this work is being done because consumers want to know that the animals raised for meat have had a good quality of life.

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Evolution of Beef Cattle Farming

Video: Evolution of Beef Cattle Farming

The Clear Conversations podcast took to the road for a special episode recorded in Nashville during CattleCon, bringing listeners straight into the heart of the cattle industry. Host Tracy Sellers welcomed rancher Steve Wooten of Beatty Canyon Ranch in Colorado for a wide-ranging discussion that blended family history and sustainability, particularly as it relates to the future of beef production.

Sustainability emerged as a central theme of the conversation, a word that Wooten acknowledges can mean very different things depending on who you ask. For him, sustainability starts with the soil. Healthy soil produces healthy grass, which supports efficient cattle capable of producing year after year with minimal external inputs. It’s an approach that equally considers vegetation, animal efficiency, and long-term profitability.

That philosophy aligned naturally with Wooten’s involvement in the U.S. Roundtable for Sustainable Beef, where he served as a representative for the Colorado Cattlemen’s Association. The roundtable brings together the entire beef supply chain—from producers to retailers—along with universities, NGOs, and allied industries. Its goal is not regulation, Wooten emphasized, but collaboration, shared learning, and continuous improvement.