Program will track welfare-related comfort behaviors like stretching, preening and dustbathing as well as production-related behaviors like eating and drinking.

February 9, 2022

2 Min Read
UTIA-poultry animal welfare.jpg
In his lab, Yang Zhao, assistant professor in the UTIA Department of Animal Science, researches welfare of broilers in production.UTIA

A research team from the University of Tennessee Institute of Agriculture has been awarded $1 million to create and implement a computer vision system to monitor poultry production. The grant was funded by the Agriculture and Food Research Initiative, a competitive grants program of the USDA National Institute of Food and Agriculture. 

Precision livestock farming systems have been implemented on larger animals for some time to monitor things like activity, agitation and other indications of animal stress and welfare; however, researchers say it has been more difficult to monitor poultry, as they are much smaller and their populations are higher in production systems. This project involves creating a computer vision system to track animal-based measures for poultry in real time. 

Using light-weight deep learning and algorithms to identify individual birds, the program will track welfare-related comfort behaviors like stretching, preening and dustbathing as well as production-related behaviors like eating and drinking. The researchers will then develop a benchmark database with detailed notes on the birds' behaviors. At an estimated cost of $2,500 per house, the computer vision system is both practical and affordable for broiler growers. The artificial intelligence and video image analysis will allow researchers to examine the interactions of the poultry's animal-based measures with management factors and collect baseline data. 

"Despite strong interest in PLF for poultry farming across the world, few systems have been developed for the commercial production environments," said Yang Zhao, lead investigator and an assistant professor in the UTIA Department of Animal Science. "This project provides us timely supports to develop an affordable PLF system that may assist broiler growers to automatically collect bird behavioral responses and better manage the flocks at commercial farms. With collaborations among researchers, Extension specialists and industry allies, this work may help further enhance the impact of the UT Precision Livestock Farming program in Tennessee, the United States and the world."

Zhao and his team expect to demonstrate the system in 2025. 

Researchers from UTIA include Yang Zhao and Maria Prado, also of the department of animal science, as well as Robert Burns, Hao Gan, Shawn Hawkins and Daniel Berckmans, of the department of biosystems engineering and soil science. Hairong Qi, from the UT department of electrical engineering and computer science, is also assisting on the project. 

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