Evaluating Alternatives to Locomotion Scoring for Detecting Lameness in Pasture-Based Dairy Cattle in New Zealand: In-Parlour Scoring

SIMPLE SUMMARY: Lameness in dairy cows is a significant challenge globally. Early detection accompanied by effective treatment can reduce the number of cows that are lame and the impact of lameness. Currently, locomotion scoring by observing the gait posture of cows is the most widely used method of detecting lame cows. However, its use is limited, especially in pasture-based production systems like in New Zealand. One possible alternative to locomotion scoring is observing and recording cows for indicators of lameness while cows are being milked. We recorded the presence of four indicators (shifting weight, abnormal weight distribution, swollen heel or hock joint, and overgrown hoof) on two dairy farms in New Zealand. Two or more indicators were more useful predictors of higher locomotion scores (lameness). However, more results on more farms are needed before the in-parlour scoring procedure can be recommended as an alternative to locomotion scoring in pasture-based dairy cattle. ABSTRACT: Earlier detection followed by efficient treatment can reduce the impact of lameness. Currently, locomotion scoring (LS) is the most widely used method of early detection but has significant limitations in pasture-based cattle and is not commonly used routinely in New Zealand. Scoring in the milking parlour may be more achievable, so this study compared an in-parlour scoring (IPS) technique with LS in pasture-based dairy cows. For nine months on two dairy farms, whole herd LS (4-point 0–3 scale) was followed 24 h later by IPS, with cows being milked. Observed for shifting weight, abnormal weight distribution, swollen heel or hock joint, and overgrown hoof. Every third cow was scored. Sensitivity and specificity of individual IPS indicators and one or more, two or more or three positive indicators for detecting cows with locomotion scores ≥ 2 were calculated. Using a threshold of two or more positive indicators were optimal (sensitivity > 92% and specificity > 98%). Utilising the IPS indicators, a decision tree machine learning procedure classified cows with locomotion score class ≥2 with a true positive rate of 75% and a false positive rate of 0.2%. IPS has the potential to be an alternative to LS on pasture-based dairy farms.