Lameness detection based on multivariate continuous sensing of milk yield, rumination, and neck activity.

Abstract

The objective of this study was to develop and validate a mathematical model to detect clinical lameness based on existing sensor data that relate to the behavior and performance of cows in a commercial dairy farm. Identification of lame (44) and not lame (74) cows in the database was done based on the farm's daily herd health reports. All cows were… (More)
DOI: 10.3168/jds.2012-6188

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Cite this paper

@article{Hertem2013LamenessDB, title={Lameness detection based on multivariate continuous sensing of milk yield, rumination, and neck activity.}, author={Tom Van Hertem and Ephraim Maltz and Aharon Antler and Carlos Eduardo Bites Romanini and Stefano Viazzi and Claudia Bahr and Andr{\'e}s Schlageter-Tello and C. Lokhorst and Daniel Berckmans and Ilan Halachmi}, journal={Journal of dairy science}, year={2013}, volume={96 7}, pages={4286-98} }