The project is one of 14 projects to receive a share of £9m funding from the Biotechnology and Biological Sciences Research Council (BBSRC) and Department for Environment, Food and Rural Affairs (Defra) as part of a major initiative to combat endemic livestock disease. It is a collaboration of UoB researchers in veterinary medicine, animal behaviour, computer vision and AI, led by Professor Andrew Dowsey from Bristol Veterinary School.
Professor Dowsey and colleagues plan to use AI in order to monitor social interactions of cattle which could indicate developing mastitis or lameness – two of the most significant diseases affecting the UK dairy industry.
While technologies do exist which automate the detection of disease in dairy cows, these tend to focus on observable symptoms which are associated with later stages of disease, however Professor Dowsey and colleagues want to see if they can identify diseases at an early stage by monitoring social interactions using AI.
Professor Dowsey said: “A cow’s response to infection or trauma is to reduce behaviours which are not immediately essential to survival, such as social interactions. In a recent study we found that social exploration, the grooming of others, and receiving headbutts were all lower in cows with early-stage mastitis (Caplen & Held, 2021), so we think social behaviour changes could be early predictors of disease.”
Detecting social behaviour changes is difficult for a busy farmer, but is possible when monitoring them at key points such as queuing for milking or feeding time.