Agricultural Research Grant Awardee 2023

Bovine clinical mastitis, an inflammation of the milk-producing gland of cattle, is economically the most devastating disease worldwide, resulting in significant loss of milk production. This stage of the disease can be detected visually and through laboratory tests. Notably, the preceding stage is asymptomatic subclinical mastitis and challenging to diagnose. If the detection of this stage is unsuccessful, the animal progress to clinical mastitis and results in enormous economic loss to the farmer. Thus, our proposal aims to adopt a combinatorial approach of knowledge from Veterinary Science, Infrared Thermography, and Artificial Intelligence for early diagnosis of subclinical mastitis. Our approach is based on measuring the variation in the body temperature arising from infections/injury/insults and converted to a heat signature indicative of inflammation or physiological changes for early therapeutic intervention. Additionally, effective and early diagnosis by Veterinarians will enable them to design better preventative and management strategies to reduce the incidence of subclinical and clinical mastitis.