Individual identification model and method for estimating social rank among herd of dairy cows using YOLOv5

Abstract

Animals typically have a hierarchical relationship called social rank. For dairy cows, this rank is particularly important in agriculture because it affects milk production, disease, and the accuracy of estrus detection. The social rank of dairy cows has been studied for a long time; it is determined manually by monitoring the behavior of dairy cows, and this requires a significant amount of time and experience. Thus, in this study, a method for automatically estimating the social rank of a herd using video images obtained from cameras is proposed. In particular, the method can automatically determine the social ranking of all cows by extracting and analyzing the fighting behavior depicted in the video images.Specifically, we used YOLOv5, an object detection model, to identify individual cows in a herd of eight cows captured by utilizing surveillance cameras. We obtained the coordinates of each individual and calculated the distance between them. Next, to extract fighting behaviors related to tank occupancy, we classified and tracked behaviors based on changes in the coordinates of each individual in each video frame. We focused on the time when the distance between individuals became small in the food container.The accuracy of the proposed model showed a high fit rate for all classes. The final estimated rankings were consistent with the expert rankings for seven out of eight animals. This showed that social rankings can be automatically obtained from video images.