45 Imaging and Phenotyping Technologies for Poultry Welfare Evaluation

• Published in: Journal of animal science Vol. 100; no. Supplement_2; p. 202
• Main Author: Chai, Lilong
• Format: Journal Article
• Language: English
• Published: US Oxford University Press 22.10.2022
• Subjects: ADDENDA TO 2022 MIDWEST SECTION MEETING ABSTRACTS
• ISSN: 0021-8812; 1525-3163
• DOI: 10.1093/jas/skac064.343

United States is currently the world’s largest broiler producer and the second largest egg producer (e.g., poultry and eggs had a sale value of $40 billion in 2021), but poultry and egg productions are facing grand challenges of animal welfare concerns, food safety issues, and environmental impacts. The rapid growth rate of broilers is associated with welfare concerns such as leg issues and lameness. Broilers with lameness suffer behavior restrictions, physical discomforts, and impingement of fundamental freedoms. Those welfare concerns have triggered the attention of the general public and the food industry to improve broiler well-being, and well-being evaluation. Animal welfare evaluation is currently performed manually by farm workers daily or occasionally in the poultry houses, which is time consuming, labor intensive, and subject to human errors. This task calls for the design of an automated system that can monitor poultry welfare automatically. Sensing technologies, such as ultra-wideband, radio frequency identification, accelerometer, and computer vision-based monitoring, have been and are being adapted and tested for livestock and poultry farming systems to aide well-being evaluation. Computer vision-based phenotyping technologies have been tested efficient in monitoring large animals such as cattle and pigs. However, it is technically challenging to monitor smaller animals such as broiler and layer chickens. Researchers at the University of Georgia are developing specific imaging and phenotyping technologies (e.g., deep learning models) for monitoring/tracking floor distribution patterns of broiler chickens and individual birds’ moving in different zones of feeding, drinking, and resting. The imaging technologies have also been applied to monitor laying hen’s behaviors of perching, pecking, and floor egg laying in the cage-free houses. Those imaging and phenotyping technologies will be further innovated for developing integrative sensing systems to evaluate poultry welfare indicators in commercial broiler and cage-free layer houses.