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An Efficient Single-Person Technique for Milk Sampling from Laboratory Mice
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Inferring relationships between somatic cell score and milk yield using simultaneous and recursive models.

X-L Wu1, B Heringstad, Y-M Chang

  • 1Department of Animal Sciences, University of Wisconsin, Madison 53706, USA. nickwu@ansci.wisc.edu

Journal of Dairy Science
|June 22, 2007
PubMed
Summary

This study reveals significant negative impacts of somatic cell score on milk yield in Norwegian Red cows, with effects varying by lactation stage and yield level. Bayesian analysis favored models accounting for these complex relationships.

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Area of Science:

  • Animal Genetics and Breeding
  • Dairy Science
  • Statistical Genetics

Background:

  • Somatic cell score (SCS) negatively impacts milk yield and quality in dairy cows.
  • Understanding the dynamic interplay between milk yield and SCS is crucial for genetic improvement and herd management.
  • Previous models may not fully capture the complex, potentially reciprocal, relationships and population heterogeneity.

Purpose of the Study:

  • To extend existing simultaneous and recursive models using Bayesian analysis to account for population heterogeneity.
  • To infer the relationships between milk yield and somatic cell scores in Norwegian Red cows.
  • To compare the performance of extended Bayesian models against traditional mixed models.

Main Methods:

  • Bayesian analysis utilizing Markov chain Monte Carlo (MCMC) methods.
  • Extension of the simultaneous and recursive model proposed by Gianola and Sorensen (2004).
  • Analysis of test-day records for milk yield and somatic cell score from first-lactation Norwegian Red cows (first 120 days).

Main Results:

  • Significant negative direct effects of SCS on milk yield were observed.
  • Small reciprocal effects of milk yield on SCS were detected.
  • Direct effects were more pronounced in the early lactation period (first 60 days).
  • Bayesian model selection favored simultaneous and recursive models over mixed models lacking these considerations.
  • Estimated effects were yield-dependent, being larger in higher-producing cows.

Conclusions:

  • The extended Bayesian simultaneous and recursive models provide a superior framework for analyzing milk yield and SCS relationships, accounting for population heterogeneity.
  • Somatic cell score exerts a substantial negative influence on milk yield, with variations based on lactation stage and cow's production level.
  • Heritability estimates were consistent across models, but genetic correlations showed considerable model-dependent differences, highlighting the importance of appropriate model selection.