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1 Utrecht University, Department of Herd Health and Reproduction, Yalelaan7 3584 CL Utrecht, The Netherlands
2 The Upjohn Company, Genevestraat 10 1140 Brussels, Belgium
3 Institute for Animal Science and Health, Research Branch Zeist, PO Box 501 3700 AM Zeist, The Netherlands
A model, based on automatically collected data, was developed for detection of subclinical mastitis. The logistic regression model was based on the following variables: milk electrical conductivity, milk production, parity, and DIM. Subclinical mastitis was defined as a minimal period of 1 wk in which the SCC was >500 x 103 cells/ml. In contrast, periods were defined as healthy if the SCC was <200 x l03 cells/ml.
The resulting model had a sensitivity of 55% and specificity of 90% for individual milkings. For periods of 14 milkings, sensitivity was 54% and specificity 92% when the threshold for that period was >6 electrical conductivity signals for high SCC.
Based on these test characteristics, the model could be used as an initial screening tool in a herd with a high incidence of subclinical mastitis. Cows with a signal would have a higher probability of being diseased than the total population. In such herds. separation of milk from the signaled cows might be a possible management strategy to reduce the SCC in the bulk milk tank.
Key Words: subclinical mastitis • detection • electrical conductivity • somatic cell count
Submitted on May 23, 1994
Accepted on December 16, 1994
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