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Estimation of genetic parameters for dairy traits and somatic cell score in the first 3 parities using a random regression test-day model in French Alpine goats

Abstract : Lactation curve shape can affect an animal's health, feed requirements, and milk production throughout the year. We implemented a random regression model for the genetic evaluation of lactation curve shapes of dairy traits in French Alpine goats for their first 3 parities. Milk, fat, and protein yields, fat and protein contents, somatic cell score, and fat/protein ratio were considered. The data consisted of test-day records from 49,849 first lactation Alpine goats during their first 3 lactations. The reference model used a Legendre polynomial of order 2 for each parity to describe the genetic and permanent environmental effects, and was compared with a model that combined the second and third parities. A rank reduction of the variance-covariance matrix was also performed using an eigenvalue decomposition for each parity from the 2 models. Genetic parameters were consistent between the models tested. With a reduction to rank 2 and combining the second and third parities, the first 2 principal components correctly summarized the genetic variability of milk yield level and persistency, with a near-nil correlation between the 2, and with a much shorter computation time than the reference model. A favorable correlation of +0.43 between milk yield persistency and fat/protein ratio persistency at the beginning of the lactation was found from buck estimated breeding values.
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https://hal.inrae.fr/hal-02793225
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Submitted on : Friday, June 5, 2020 - 9:29:11 AM
Last modification on : Wednesday, February 2, 2022 - 6:02:04 PM

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M. Arnal, Helene Larroque, H. Leclerc, Vincent Ducrocq, Christèle Robert-Granié. Estimation of genetic parameters for dairy traits and somatic cell score in the first 3 parities using a random regression test-day model in French Alpine goats. Journal of Dairy Science, American Dairy Science Association, 2020, 103 (5), pp.4517-4531. ⟨10.3168/jds.2019-17465⟩. ⟨hal-02793225⟩

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