Food Science Unit Precision Livestock Farming
Van Nuffel A.,Food Science Unit Precision Livestock Farming |
Saeys W.,Catholic University of Leuven |
Sonck B.,Belgium Institute for Agricultural and Fisheries Research |
Vangeyte J.,Food Science Unit Precision Livestock Farming |
And 3 more authors.
Livestock Science | Year: 2015
To support herdsmen in finding the lame cows on their herds, several automated systems that measure lameness related cow features such as gait patterns, are being developed. Most of these systems are able to distinguish between non-lame and severely lame cows. Detecting mildly lame cows in an early stage of lameness however seems challenging. Inspired by the approach used in human gait research, new variables that measure the inconsistency in stride-to-stride variables were tested using cow gait and were able to show differences between a group of non-lame and a group of mildly lame cows. In order to investigate the added value of these inconsistency variables in detecting mildly lame cows, two new lameness detection models were build: one using solely basic gait variables and a second model using both basic and the new gait inconsistency variables. The second model using the gait inconsistency variables outperformed the model based on only basic gait variables by far in detecting the mildly lame cows with a sensitivity of 88% and a specificity of 87%. These results support the suggestion of incorporating such gait inconsistency variables into lameness detection models. Further validation of these gait inconsistency variables should be investigated using longitudinal studies where cows developing lameness and recovering from it are monitored daily. © 2015 Elsevier B.V.