Efficient lameness detection is crucial in maintaining health, welfare and productivity of dairy cattle. This study evaluated a fully automated 2-dimensional imaging system employing machine learning to provide real-time mobility score predictions. The system was tested on eleven commercial farms, showing a performance comparable to that of experienced human assessors in detecting lame cows and cows with foot lesions. When using daily mobility scores generated over 30 days before trimming, the system’s accuracy was improved and outperformed the human assessor. This advanced technological application offers potential for early detection of lame cows and effective management of lameness in dairy herds.
