Predicting bull mounting behavior using classification algorithms

Authors

  • K. M. Abell Diagnostic Medicine and Pathobiology, Kansas State University, Manhattan, KS 66506
  • B. J. White Clinical Sciences, Kansas State University, Manhattan, KS 66506
  • R. L. Larson Clinical Sciences, Kansas State University, Manhattan, KS 66506
  • M. E. Theurer Kansas State University, Manhattan, KS 66506
  • D. K. Hardin Veterinary and Biomedical Sciences, University of Nebraska-Lincoln, Lincoln, NE 68588
  • R. R. Randle Veterinary and Biomedical Sciences, University of Nebraska-Lincoln, Lincoln, NE 68588

DOI:

https://doi.org/10.21423/aabppro20163473

Keywords:

bull mounting, reproductive, beef cattle, records, animal behavior, accelerometer data, algorithm

Abstract

Data from multiple-sire beef cattle pastures have shown variability exists among the number of calves sired per bull. The reason(s) for the variability is unknown. Successful investigation of possible reasons requires accurate recording and evaluation of bull behavior. The purpose of this study was to assess the accuracy of classifying bull mounting events in a multiple-sire pasture using accelerometer data and classification algorithms.

Cover image of the 49th Conference Proceedings: An image of a herd of Angus cattle grazing in a field at dusk. Yellow background.

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Published

2016-09-15

Issue

2016

Section

Research Summaries 3

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