title: Genetic parameters for test-day yield of milk, fat and protein in buffaloes estimated by random regression models.
abstract: The test-day yields of milk, fat and protein were analysed from 1433 first lactations of buffaloes of the Murrah breed, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, born between 1985 and 2007. For the test-day yields, 10 monthly classes of lactation days were considered. The contemporary groups were defined as the herd-year-month of the test day. Random additive genetic, permanent environmental and residual effects were included in the model. The fixed effects considered were the contemporary group, number of milkings (1 or 2 milkings), linear and quadratic effects of the covariable cow age at calving and the mean lactation curve of the population (modelled by third-order Legendre orthogonal polynomials). The random additive genetic and permanent environmental effects were estimated by means of regression on third- to sixth-order Legendre orthogonal polynomials. The residual variances were modelled with a homogenous structure and various heterogeneous classes. According to the likelihood-ratio test, the best model for milk and fat production was that with four residual variance classes, while a third-order Legendre polynomial was best for the additive genetic effect for milk and fat yield, a fourth-order polynomial was best for the permanent environmental effect for milk production and a fifth-order polynomial was best for fat production. For protein yield, the best model was that with three residual variance classes and third- and fourth-order Legendre polynomials were best for the additive genetic and permanent environmental effects, respectively. The heritability estimates for the characteristics analysed were moderate, varying from 0·16±0·05 to 0·29±0·05 for milk yield, 0·20±0·05 to 0·30±0·08 for fat yield and 0·18±0·06 to 0·27±0·08 for protein yield. The estimates of the genetic correlations between the tests varied from 0·18±0·120 to 0·99±0·002; from 0·44±0·080 to 0·99±0·004; and from 0·41±0·080 to 0·99±0·004, for milk, fat and protein production, respectively, indicating that whatever the selection criterion used, indirect genetic gains can be expected throughout the lactation curve.
authors.affiliation: Department of Animal Science, São Paulo State University, Jaboticabal 14884 900, SP, Brazil.
authors.forename: Rúsbel R
authors.initials: RR
authors.lastname: Aspilcueta-Borquis
authors.forename: Francisco R
authors.initials: FR
authors.lastname: Araujo Neto
authors.forename: Fernando
authors.initials: F
authors.lastname: Baldi
authors.forename: Daniel J A
authors.initials: DJ
authors.lastname: Santos
authors.forename: Lucia G
authors.initials: LG
authors.lastname: Albuquerque
authors.forename: Humberto
authors.initials: H
authors.lastname: Tonhati
mesh_terms: D000818:Animals; D001938:Brazil; D002020:Buffaloes / Q000235:genetics* / Q000378:metabolism; D005223:Fats / Q000032:analysis*; D005260:Female; D014644:Genetic Variation; D007774:Lactation / Q000235:genetics*; D008892:Milk / Q000737:chemistry*; D008894:Milk Proteins / Q000032:analysis*; D015233:Models, Statistical; D019655:Quantitative Trait, Heritable; D012044:Regression Analysis
chemical_list: D005223:Fats; D008894:Milk Proteins