Automating management of teat tissue condition in dairy cows through machine learning
Mastitis, a significant concern in the dairy industry due to marked reduction in milk production and the reduced immune system for dairy cattle, is assessed through physical examinations of a dairy cow’s teat health. This costly, time-consuming approach is error prone and labor intensive. This project proposes first to use a multi-modality machine learning system to measure for short term changes in teat tissue while also developing an image and video based deep learning classifier to predict long-term changes. The sensitivity and specificity of the machine learning system will be compared with the traditional, manual approach. Results will potentially impact current milk harvesting strategies, the advancement of udder health, animal well-being, and sustainability of farms with local impact in the NYS dairy industry and across the globe.