Prediction of body condition in Jersey dairy cattle from 3D-images using machine learning techniques.

The body condition of dairy cows is a crucial health and welfare indicator that is widely acknowledged in dairy cattle management. Routine recording of high-quality body condition phenotypes is required for adaptation in dairy herd management. The use of machine learning to predict the body condition of dairy cows from 3D images can offer a cost-effective approach to the current manual recording performed by technicians. We aimed to build a reliable prediction, based on data from 808 Jersey cows with 2,253 body condition phenotypes from three commercial herds in Denmark. We tested different machine-learning models. All models showed high prediction accuracy, and comparable levels with other published studies on Holstein cows. In a validation test across project herds, prediction accuracy ranged between 87% and 96%.