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 optimize 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 influence 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.
| Original language | English |
|---|---|
| Journal | Journal of Dairy Science |
| Volume | 77 |
| Issue number | 10 |
| Pages (from-to) | 2975-2993 |
| Number of pages | 19 |
| ISSN | 0022-0302 |
| DOIs | |
| Publication status | Published - 1 Jan 1994 |
Keywords
- accumulated number of CQ in the previous lactation (four levels: 0, 1, 2 and ≥3)
- accumulated number of diagnosed clinical quarters in the current lactation from the beginning of the lactation (t = 0) through month t – 1 (four levels: 0, 1, 2 and ≥3)
- binary variable indicating that clinical mastitis was diagnosed in at least one quarter ≥1) or in none of the quarters (0) in month t of the current lactation
- CQ
- DP
- DQ
- dynamic programming
- economics
- hierarchic Markov process
- HMP
- mastitis
- PQ
- replacement