Evaluating Alternatives to Locomotion Scoring for Detecting Lameness in Pasture-Based Dairy Cattle in New Zealand: In-Parlour Scoring.
Authors: Werema Chacha W, Yang Dan A, Laven Linda J, Mueller Kristina R, Laven Richard A
Journal: Animals : an open access journal from MDPI
Summary
# Editorial Summary Detecting lameness early in pasture-based dairy systems remains challenging, as traditional locomotion scoring is difficult to implement routinely on grazing cattle and may miss cases before clinical signs become obvious. Researchers in New Zealand evaluated whether in-parlour scoring (IPS)—assessing weight-shifting, abnormal weight distribution, swollen joints, and hoof overgrowth whilst cows are restrained for milking—could reliably identify lame animals compared to standard locomotion scoring conducted in the paddock. Over nine months across two farms, every third cow underwent both assessments, revealing that using two or more positive IPS indicators achieved excellent sensitivity (>92%) and specificity (>98%) for detecting cows with locomotion scores of 2 or above on a 0–3 scale; machine learning analysis further refined these thresholds, achieving a 75% true positive rate with minimal false positives (0.2%). The practical advantage lies in integrating lameness detection into existing milking routines without additional farm visits, potentially improving early identification and treatment rates in systems where traditional scoring is impractical or unreliable. For equine professionals involved in pasture-based settings, this approach demonstrates how working within existing management constraints—rather than against them—can enhance welfare monitoring and intervention timing.
Read the full abstract on PubMed
Practical Takeaways
- •In-parlour assessment during milking offers a practical, high-accuracy alternative to pasture-based locomotion scoring for early lameness detection in dairy operations
- •Using a threshold of two or more positive indicators optimises both sensitivity and specificity, making the system reliable for identifying lame animals requiring treatment
- •Integration of in-parlour scoring into routine milking workflows could enable more consistent lameness monitoring without requiring animals to be assessed while grazing
Key Findings
- •In-parlour scoring (IPS) with two or more positive indicators achieved >92% sensitivity and >98% specificity for detecting locomotion scores ≥2 in pasture-based dairy cattle
- •Machine learning decision tree using IPS indicators classified lame cows (locomotion score ≥2) with 75% true positive rate and 0.2% false positive rate
- •IPS is more practical than traditional locomotion scoring on pasture-based dairy farms in New Zealand where locomotion scoring is not routinely used
- •IPS indicators assessed shifting weight, abnormal weight distribution, swollen joints, and overgrown hooves during routine milking