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Monitoring Broiler Group Distribution Index with the Machine Vision-Based Technology

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  2021 ASABE Annual International Virtual Meeting  2100856.(doi:10.13031/aim.202100856)
Authors:   Yangyang Guo, Lilong Chai
Keywords:   Broiler chicken; animal health and welfare; group behaviors; precision farming

Abstract. Animal behaviors are valuable information for analyzing indicators of animal health/well-being, welfare, and production. The monitoring of animal behavior information is conducive to the construction of welfare breeding systems and the application of modern technology in the industry. Normally, a poultry house contains multiple individuals, and individual behavior cannot directly reflect the welfare status of the poultry flock. In this study, the group distribution index (GDI, e.g., distribution index of animals in each zone of feeding, drinking, and resting and the group activity index) were defined to reflect the general behavioral or welfare status of the group. To assess the method, broiler chickens‘ images from d1 to d49 (top-view video data of group) were collected from the research broiler houses. In the video data, we divided each pen into a feeding, a drinking, and an activity or resting zone. Firstly, machine learning technology was used to extract the target area of broiler chickens in the video. Secondly, the distribution of feeding, drinking, and activity/rest zones was calculated, respectively. Finally, the distribution of broiler chicken populations was obtained from 6 am to 6 pm on d2, d9 and d16. The research can be used to detect the group behavior of chicken flocks, which is conducive to precise management.

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