Somatic cell count distributions during lactation predict clinical mastitis

M. J. Green*, L. E. Green, Y. H. Schukken, A. J. Bradley, E. J. Peeler, H. W. Barkema, Y. De Haas, V. J. Collis, G. F. Medley

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

79 Citations (Scopus)


This research investigated somatic cell count (SCC) records during lactation, with the purpose of identifying distribution characteristics (mean and measures of variation) that were most closely associated with clinical mastitis. Three separate data sets were used, one containing quarter SCC (n = 1444) and two containing cow SCC (n = 933 and 11,825). Clinical mastitis was defined as a binary outcome, present or absent, for each lactation, and SCC were log (base 10) transformed. A generalized linear mixed model within a Bayesian framework was used for analysis. Parameters were estimated using Markov Chain Monte Carlo with Gibbs sampling. Results from the 3 data sets were similar. Increased maximum and standard deviation log SCC during lactation, rather than increased geometric mean, were the best overall indicators of clinical mastitis. Distributions of SCC were also investigated separately for different mastitis pathogens. Increased maximum log SCC was associated with clinical mastitis caused by all pathogen types. Increased standard deviation log SCC was associated with Staphylococcus aureus, and Streptococcus uberis clinical mastitis and increased coefficient of variation log SCC (standard deviation divided by mean) was associated with Escherichia coli clinical mastitis. Increased geometric mean lactation SCC was associated with an increased risk of Staph. aureus clinical mastitis but a reduced risk of E. coli clinical mastitis. Our results suggest that using measures of variation and maximum cow SCC would enhance the accuracy of predicting clinical mastitis, compared with geometric mean SCC, and therefore improve genetic programs that aim to select for clinical mastitis resistance. The results are also consistent with low SCC increasing susceptibility to some mastitis pathogens.

Original languageEnglish
Pages (from-to)1256-1264
Number of pages9
JournalJournal of Dairy Science
Issue number5
Publication statusPublished - May 2004

Bibliographical note

Funding Information:
We would like to thank the farmers and herdspersons involved in the study, the Wood Veterinary Group, Gloucester, UK, and C. Poetzch for collating data set 2. We thank NRS, The Netherlands, for providing milk recording data for data set 3. Financial support came from Leo Animal Health UK Ltd , Milk Development Council , UK, and Roche Vitamins , UK. M. J. Green is supported by a BBSRC case studentship.


  • Mastitis
  • Somatic cell count

ASJC Scopus subject areas

  • Food Science
  • Animal Science and Zoology
  • Genetics


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