Economic Impact of Abortions in Dairy Cow Herds
This study aimed to explore Markov decision methods in order to solve the problem of dairy cow replacement, adding the special characteristics of two types of abortions due to different sanitary reasons that influence the economic, production, and reproduction performance of these animals. The model...
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Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-07-01
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Series: | Veterinary Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2306-7381/12/7/645 |
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Summary: | This study aimed to explore Markov decision methods in order to solve the problem of dairy cow replacement, adding the special characteristics of two types of abortions due to different sanitary reasons that influence the economic, production, and reproduction performance of these animals. The model was successfully validated against other models published in the literature. Python code v.3.13 was used to solve the problem and to ease future extensions with the inclusion of new variables. The results constitute tools that allow the veterinarian to explore more realistic scenarios by running a Markov simulation model that avoids the complexities leading to the problem of dimensionality in dynamic optimization models. In our study, the economic value of the herd considering RA and NLA abortions shows that the maximum net benefit is USD 178.77 per cow, and non-pregnant cows are slaughtered upon reaching six months of lactation, a value that is within the range of values reported by the literature that we have identified. At the optimum, the replacement model extended with abortion generates a difference of USD 0.69 per cow per month compared to the model that does not include the special abortion features. The changes in the net present value of each cow according to the month of culling depend on the variability of milk income and slaughter value and heifers’ replacement values, suggesting that any measure that seeks to improve the economic benefit of dairy cows should take greater account of these variables. |
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ISSN: | 2306-7381 |