Genetic parameters for first lactation dairy traits in the Alpine and Saanen goat breeds using a random regression test-day model.

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 gen

SUBMITTER: Arnal M 

PROVIDER: S-EPMC6693143 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature