Persistence in milk, fat and protein production of primiparous Holstein cows by random regression models

• Autor(a) principal: Biassus,Igor de Oliveira
• Data de Publicação: 2010
• Outros Autores: Cobuci,Jaime Araújo, Costa,Claudio Napolis, Rorato,Paulo Roberto Nogara, Braccini Neto,José, Cardoso,Leandro Lunardini
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista Brasileira de Zootecnia (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982010001200009
• topic: genetic correlation; heritability; Legendre polynomials; random regression model; selection

Total numbers of 56,508, 35,091 and 8,326 records of milk, fat, and protein test-day yields, respectively, were used to estimate genetic parameters for six persistency measures on milk, fat and protein productions of Holstein cows reared in Minas Gerais state. Covariance components for additive genetic effects and permanent environmental effects were estimated by REML in random regression models using Legendre polynomials from the third to the sixth order. Overall, models with the highest orders of Legendre polynomials showed the best quality of adjustments of these productive records. Heritability estimates obtained by the models for persistence in milk, fat, and protein yields ranged from 0.04 to 0.32, from 0.00 to 0.23, and from 0.00 to 0.27, respectively. Values of genetic correlation estimates between persistence and total 305-day milk, fat, and protein yields ranged from -0.38 to 0.54, from -0.39 to 0.97, and from -0.78 to 0.67, respectively. Persistence measurement proposed by Jakobsen (PS2) is preferential for using in further genetic evaluations for persistence in milk, fat and protein yields of Holstein cows in Minas Gerais state.