Evaluation of predictive models to determine final outcome for feedlot cattle based on information available at first treatment for bovine respiratory disease

Authors

  • L. Heinen Beef Cattle Institute, Kansas State University, Manhattan, KS, 66506
  • D. E. Amrine Beef Cattle Institute, Kansas State University, Manhattan, KS, 66506
  • R. L. Larson Beef Cattle Institute, Kansas State University, Manhattan, KS, 66506
  • B. J. White Beef Cattle Institute, Kansas State University, Manhattan, KS, 66506

DOI:

https://doi.org/10.21423/aabppro20228656

Abstract

Bovine respiratory disease (BRD) is the costliest health condi­tion affecting feedyards in North America. Accurate identifica­tion of severe disease has the potential to aid in establishing an intervention to prevent a case fatality in individual animals. The study objective was to evaluate the diagnostic ability of predictive models to determine the probability a calf at first BRD treatment would finish the feeding period with the group or incur a negative outcome (railed or died). Additional com­parisons were made to evaluate potential benefits to predictive model performance by the addition of weather data, utilization of a data balancing technique, and creation of models for indi­vidual feedlots.

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Published

2023-07-17

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