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Related Experiment Videos

Somatic cell count distributions during lactation predict clinical mastitis.

M J Green1, L E Green, Y H Schukken

  • 1Ecology and Epidemiology Group, Department of Biological Sciences, University of Warwick, Coventry, UK. martingreen1000@ntlworld.com

Journal of Dairy Science
|August 5, 2004
PubMed
Summary

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Measures of variation and maximum somatic cell count (SCC) during lactation, not the average SCC, best predict clinical mastitis. These findings can improve genetic selection for mastitis resistance in dairy cows.

Area of Science:

  • Veterinary Medicine
  • Animal Science
  • Dairy Science

Background:

  • Somatic Cell Count (SCC) is a key indicator of bovine udder health.
  • Understanding SCC distribution characteristics is crucial for predicting clinical mastitis.
  • Current methods may not fully capture the predictive power of SCC variations.

Purpose of the Study:

  • To identify somatic cell count (SCC) distribution characteristics most associated with clinical mastitis.
  • To compare the predictive value of mean SCC versus measures of variation and maximum SCC.
  • To inform genetic selection programs for improved mastitis resistance.

Main Methods:

  • Analysis of three datasets with quarter and cow SCC records.
  • Clinical mastitis defined as a binary outcome.

Related Experiment Videos

  • Generalized linear mixed model within a Bayesian framework using Markov Chain Monte Carlo with Gibbs sampling.
  • Log (base 10) transformation of SCC data.

    • Main Results:

    • Increased maximum and standard deviation of log SCC during lactation were superior indicators of clinical mastitis compared to the geometric mean.
    • Maximum log SCC correlated with mastitis from all pathogen types.
    • Standard deviation and coefficient of variation of log SCC showed specific associations with different mastitis pathogens (e.g., Staphylococcus aureus, Streptococcus uberis, Escherichia coli).

    Conclusions:

    • Measures of variation and maximum SCC enhance clinical mastitis prediction accuracy over geometric mean SCC.
    • These findings can refine genetic programs for selecting cows resistant to clinical mastitis.
    • Results suggest that low SCC may increase susceptibility to certain mastitis pathogens.