WELL-CALF: optimising accuracy for commercial adoption

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Calves from dairy herds are the foundation animals for dairy farms and the dairy-beef industry, but several diseases are endemic. Bovine respiratory disease (BRD) affects 11% of all calves and is the leading cause of poor performance (and mortality) in cattle <10 months of age, costing UK farmers ~£80Mp.a.(veterinary treatments, reduced lifetime productivity, mortality;Zoetis,2022). Thermal stress impacts the immune status and leaves calves more susceptible to illness(Vet Sci,2020).Integrating health and production data across a calf's life represents a significant challenge to the industry, thus management decisions are currently made without any prior knowledge of a farm or animal's disease or production status. CATL's automated monitoring solutions for health surveillance improves results but further potential for optimisation exists.The initial aims of the WELL-CALF project were to (i) develop and implement a data platform integrating health and production parameters across animal lifetime, (ii) to develop an innovative agri-engineering system for calf-rearer units integrating a novel multi-sensor platform with performance data to monitor calf health status, and (iii) to utilise advanced data analytics to classify health conditions in individuals, to facilitate rapid, individually-tailored treatment.For this project, we aim to extend and improve on the WELL-CALF project by refining prediction models for bovine respiratory disease, using advanced machine learning techniques.