Source: Michigan State University
Researchers at Michigan State University are developing a machine-learning system to better detect and manage pain in dairy calves following hot-iron disbudding, a common practice to prevent horn growth. Although veterinarians recommend multimodal pain control using local anesthesia and NSAIDs, calves vary in their pain responses, and some continue to suffer despite treatment. Using minute-by-minute activity data from commercial ear-tag sensors, the system analyzes behavioral patterns to identify calves experiencing pain.
In a preliminary study of 40 calves, the model achieved 91% overall accuracy, with 86% sensitivity and 82% specificity in distinguishing painful from non-painful animals. Notably, 25% of calves were still flagged as in pain 24 to 72 hours after disbudding, suggesting they may benefit from additional medication. Researchers aim to integrate the technology into a mobile app to help farmers and veterinarians make targeted treatment decisions, improving animal welfare, health outcomes, growth performance and public confidence in dairy practices.
Read the full story HERE: https://www.canr.msu.edu/news/improving-dairy-calf-pain-mitigation