Optimal replacement of mastitic cows determined by a hierarchical Markov process

Optimal replacement of mastitic cows determined by a hierarchical Markov process

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Article ID: iaor19991816
Country: United States
Volume: 77
Issue: 10
Start Page Number: 2975
End Page Number: 2993
Publication Date: Oct 1994
Journal: Journal of Dairy Science
Authors: , , ,
Keywords: biology, measurement, programming: dynamic
Abstract:

Farmers frequently have to decide whether to keep or to replace cows that suffer from clinical mastitis. A dynamic programming model was developed to optimise these decisions for individual cows within the herd, using the hierarchic Markov process technique. This technique provides a method to model a wide variety of cows, differing in age, productive performance, reproductive status, and clinical mastitis occurrence. The model presented was able to support decisions related to 63% of all replacements. Results – for Dutch conditions – showed the considerable impact of mastitis on expected income of affected cows. Nevertheless, in most cases, the optimal decision was to keep and to treat rather than to replace the cow. Clinical mastitis occurring in the previous lactation negligibly influenced expected income. Clinical mastitis in current lactation, especially in the current month, however, had a significant effect on expected income. Total losses caused by clinical mastitis were US$83/yr per cow. Farm level treatment, which reduced incidence by 25%, on a farm with 10 clinical quarter cases per 10,000 cow days, may cost at maximum US$27/yr per cow.

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