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Related Experiment Videos

Computing mating bull fertility from DHI nonreturn data.

J S Clay1, B T McDaniel

  • 1Department of Animal Science, North Carolina State University, Raleigh 27695-7623, USA. john-clay@ncsu.edu

Journal of Dairy Science
|June 1, 2001
PubMed
Summary
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This study developed a method to estimate bull fertility using Holstein AI mating data. Early fertility estimates accurately predicted later performance, aiding in bull selection for improved conception rates.

Area of Science:

  • Animal Science
  • Reproductive Biology
  • Dairy Cattle Genetics

Background:

  • Accurate fertility assessment is crucial for dairy herd improvement.
  • Traditional methods may not fully capture bull reproductive efficiency.
  • Developing reliable measures for bull fertility is an ongoing challenge.

Purpose of the Study:

  • To compute yearly measures of relative fertility for Holstein AI mating bulls.
  • To assess the predictive accuracy of early fertility estimates for later performance.
  • To identify factors influencing bull conception rates.

Main Methods:

  • Utilized animal model methodology with 70-day nonreturn data from U.S. DHIA (1988-1997).
  • Calculated Estimated Relative Conception Rates (ERCR) using specific variance ratios and fixed effects.

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  • Analyzed fertility estimates based on cow age, milk production, and lactation stage.

    • Main Results:

    • ERCR ranged from -18 to +13, with 90% within four units of zero for bulls with >=1000 breedings.
    • Early ERCR from >=300 matings accurately predicted later independent ERCR.
    • Fertility estimates were higher for younger cows with lower production and in late lactation.

    Conclusions:

    • The developed ERCR method provides a reliable yearly measure of bull fertility.
    • Early fertility data can effectively predict long-term bull reproductive performance.
    • ERCR offers valuable insights for genetic selection and herd management to enhance dairy cattle fertility.