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Related Experiment Videos

Dairy cattle culling patterns, explanations, and implications.

G L Hadley1, C A Wolf, S B Harsh

  • 1Department of Agricultural Economics, University of Wisconsin-River Falls, River Falls 54022, USA.

Journal of Dairy Science
|May 17, 2006
PubMed
Summary

Dairy cow culling patterns were analyzed using extensive records. Factors like calving season, milk production, and health (somatic cell count) significantly influence a cow's likelihood of being culled.

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Area of Science:

  • Dairy Science
  • Animal Husbandry
  • Veterinary Epidemiology

Background:

  • Culling is a critical management decision in dairy herds.
  • Understanding culling patterns is essential for herd profitability and longevity.
  • Previous studies have identified various factors influencing culling, but regional variations and specific predictive models are continually refined.

Purpose of the Study:

  • To analyze dairy cow culling patterns in the Upper Midwest and Northeast regions of the USA.
  • To identify individual cow and herd characteristics that predict the likelihood of culling.
  • To develop a predictive model for cow culling decisions.

Main Methods:

  • Utilized Dairy Herd Improvement (DHI) records from 1993-1999, encompassing over 7 million lactation observations.

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  • Employed a probit regression model to assess the impact of cow and herd variables on monthly culling probability.
  • Incorporated state, year, and farm effects into the model.

    • Main Results:

    • The probit model achieved high accuracy rates (79.5% in Upper Midwest, 79.9% in Northeast) in predicting individual cow culling.
    • Factors reducing culling likelihood included summer/fall calving, higher milk production and protein content, and increased milk production persistency.
    • Factors increasing culling likelihood included lower-than-average butterfat content and higher somatic cell count scores.

    Conclusions:

    • Cow and herd characteristics, alongside geographic and temporal variables, significantly influence culling decisions.
    • The developed model provides a valuable benchmark for dairy producers to understand and potentially manage culling patterns.
    • Predictive insights can aid in optimizing herd management and improving overall dairy farm efficiency.