Body condition scoring of dairy cows estimates their body reserves. Automation allows increased data availability and reduced labour costs. The aim of this study was to compare an automated (AUT) body condition score (BCS) system to manual observers on a single commercial dairy farm in south-west England. Three practising veterinary surgeons performed body condition scoring of 315 dairy cows using the agriculture and horticulture development board (AHDB) Body Condition Scorecard. AUT BCSs were obtained from two 3D cameras and compared to the BCSs recorded by the three operators. The AUT system only agreed with manual scorers at a BCS of 3. The system failed to detect cows classified as underconditioned (BCS ≤ 2.25) by any of the operators (sensitivity 0%). It also systematically underestimated the BCS of cows classified as overconditioned (BCS ≥ 3.5) by the operators. For overconditioned cows, the sensitivity of the AUT system ranged from 30.7% to 48.8% when compared with the manual operators. The AUT system also had weaker agreement with operators for Jersey cows, with Cohen's weighted kappa values of 0.28 for Jersey animals and 0.40 for Holsteins. This study used a convenience sample of animals on a single farmat a single time point, so the extent to which the findings can be more widely generalised is unclear. The AUT system failed to detect animals classified as underconditioned by the operators and underestimated the condition of cows classified as overconditioned by the operators. Currently, without improvements to the algorithm, the clinical usefulness of such an AUT system for body condition scoring is limited.
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