Estimates covariance functions to goats milk production using regression models random

• Autores: Wéverton José Lima Fonseca, Laylson da Silva Borges, Amauri Felipe Evangelista, Paulo Henrique Amaral Araújo de Sousa, Genilson Sousa do Nascimento, Carlandia Pacheco de Figueiredo, Teobaldo Florêncio de Almeida Júnior, Leandro de Oliveira Guerra, Diego Helcias Cavalcante, Severino Cavalcante de Sousa Júnior
• Localización: Nucleus Animalium, ISSN-e 2175-1463, Vol. 7, Nº. 2, 2015
• Idioma: portugués
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• Resumen

  • The aim of this review was to estimate covariance functions for the production of Alpine breeds of goat milk and Saanen using random regression models. Conventional analysis for estimating components of (co) variance and genetic parameters for growth traits are performed by finite-dimensional models, which allows the construction and use of selection indexes and mixed model equations, obtaining parameters as heritability and genetic correlation. The random regression models (MRA) enable work with characteristics of genetic lactation curves for each animal or growth that are measured repeatedly in the animal's life, called longitudinal data.