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Comparison of Models to Identify Lame Cows Based on Gait and Lesion Scores, and Limb Movement Variables

P. G. Rajkondawar^*,1, M. Liu, R. M. Dyer, N. K. Neerchal, U. Tasch, A. M. Lefcourt, B. Erez^|| and M. A. Varner^#

^* Bou-Matic, LLC, Madison, WI 53708
Department of Mathematics and Statistics, University of Maryland at Baltimore County (UMBC), Baltimore 21250
Department of Animal and Food Sciences, University of Delaware, Newark 19717
Department of Mechanical Engineering, UMBC, Baltimore 21250
^|| Agriculture Experiment Station (Central Maryland Research and Education Center), University of Maryland, Ellicott City 21042
^# Department of Animal and Avian Science, University of Maryland, College Park 20742

¹ Corresponding author: parimal{at}boumatic.com

Bovine lameness results in pain and suffering in cattle and economic loss for producers. A system for automatically detecting lame cows was developed recently that measures vertical force components attributable to individual limbs. These measurements can be used to calculate a number of limb movement variables. The objective of this investigation was to explore whether gait scores, lesion scores, or combined gait and lesion scores were more effectively captured by a set of 5 limb movement variables. A set of 700 hind limb examinations was used to create gait-based, lesion-based, and combined (gait- and lesion-based) models. Logistic regression models were constructed using 1, 2, or 3 d of measurements. Resulting models were tested on cows not used in modeling. The accuracy of lesion-score models was superior to that of gait-score models; lesion-based models generated greater values of areas under the receiving operating characteristic curves (range 0.75 to 0.84) and lower mean-squared errors (0.13 to 0.16) compared with corresponding values for the gait-based models (0.63 to 0.73 and 0.26 to 0.31 for receiving operating characteristic and mean-squared errors, respectively). These results indicate that further model development and investigation could generate automated and objective methods of lameness detection in dairy cattle.

Key Words: dairy cow lameness • automated lameness detection • gait score • lesion score

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