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- Title
Genetic parameters for first lactation dairy traits in the Alpine and Saanen goat breeds using a random regression test-day model.
- Authors
Arnal, Mathieu; Larroque, Hélène; Leclerc, Hélène; Ducrocq, Vincent; Robert-Granié, Christèle
- Abstract
Background: Random regression models (RRM) are widely used to analyze longitudinal data in genetic evaluation systems because they can better account for time-course changes in environmental effects and additive genetic values of animals by fitting the test-day (TD) specific effects. Our objective was to implement a random regression model for the evaluation of dairy production traits in French goats. Results: The data consisted of milk TD records from 30,186 and 32,256 first lactations of Saanen and Alpine goats. Milk yield, fat yield, protein yield, fat content and protein content were considered. Splines were used to model the environmental factors. The genetic and permanent environmental effects were modeled by the same Legendre polynomials. The goodness-of-fit and the genetic parameters derived from functions of the polynomials of orders 0 to 4 were tested. Results were also compared to those from a lactation model with total milk yield calculated over 250 days and to those of a multiple-trait model that considers performance in six periods throughout lactation as different traits. Genetic parameters were consistent between models. Models with fourth-order Legendre polynomials led to the best fit of the data. In order to reduce complexity, computing time, and interpretation, a rank reduction of the variance covariance matrix was performed using eigenvalue decomposition. With a reduction to rank 2, the first two principal components correctly summarized the genetic variability of milk yield level and persistency, with a correlation close to 0 between them. Conclusions: A random regression model was implemented in France to evaluate and select goats for yield traits and persistency, which are independent i.e. no genetic correlation between them, in first lactation.
- Subjects
FRANCE; LACTATION; GOAT breeds; REGRESSION analysis; MILK yield; COVARIANCE matrices; GENETIC correlations; GOAT diseases
- Publication
Genetics Selection Evolution, 2019, Vol 51, Issue 1, pN.PAG
- ISSN
0999-193X
- Publication type
Article
- DOI
10.1186/s12711-019-0485-3