Random regression models to estimate genetic parameters for test‐day milk yield in Brazilian Murrah buffaloes

Abstract

The objective of this work was to estimate covariance functions for additive genetic and permanent environmental effects and, subsequently, to obtain genetic parameters for buffalo's test-day milk production using random regression models on Legendre polynomials (LPs). A total of 17 935 test-day milk yield (TDMY) from 1433 first lactations of Murrah buffaloes, calving from 1985 to 2005 and belonging to 12 herds located in São Paulo state, Brazil, were analysed. Contemporary groups (CGs) were defined by herd, year and month of milk test. Residual variances were modelled through variance functions, from second to fourth order and also by a step function with 1, 4, 6, 22 and 42 classes. The model of analyses included the fixed effect of CGs, number of milking, age of cow at calving as a covariable (linear and quadratic) and the mean trend of the population. As random effects were included the additive genetic and permanent environmental effects. The additive genetic and permanent environmental random effects were modelled by LP of days in milk from quadratic to seventh degree polynomial functions. The model with additive genetic and animal permanent environmental effects adjusted by quintic and sixth order LP, respectively, and residual variance modelled through a step function with six classes was the most adequate model to describe the covariance structure of the data. Heritability estimates decreased from 0.44 (first week) to 0.18 (fourth week). Unexpected negative genetic correlation estimates were obtained between TDMY records at first weeks with records from middle to the end of lactation, being the values varied from -0.07 (second with eighth week) to -0.34 (1st with 42nd week). TDMY heritability estimates were moderate in the course of the lactation, suggesting that this trait could be applied as selection criteria in milking buffaloes.

Estimation of genetic parameters for test-day milk yield in Khuzestan buffalo

“…Additive genetic variances had the highest values in the early weeks of lactation, whereas permanent environmental variances were the highest in the twenty-fifth week (Figure 2). Likewise, Sesana et al (2010) compared different structures of permanent environmental variances using RRM and found higher variance estimates at early lactation in milking buffalo. Madad et al (2013b), using RRM in dairy buffalo, also reported high additive genetic variance in the early months of lactation, despite observing lower variances.…”

“…Phenotypic variance estimates were higher during the first two weeks of lactation, which decreased at the ninth week and then reached the maximum value at the thirteenth week of lactation. Based on the results of Bignardi et al (2009) and Sesana et al (2010), Figure 2. Additive genetic (A), permanent environmental (B), phenotypic (C), and residual (D) variance estimates for test-day milk yield for each week of lactation of Khuzestan buffalo, obtained with a model with nine classes of heterogeneous residual effect and orders of fit for direct additive and permanent environmental effects equal to 3.…”

Random regression models to estimate genetic parameters for test-day milk yield and composition in Iranian buffaloes

“…Negative genetic correlations for milk yield between the DIM 270 and DIM 90-180 were obtained in this study. Sesana et al (2010) reported about unexpected negative genetic correlation estimates between TDMY records in the first weeks with records from the middle to the end of lactation. Except for DIM 30 and DIM 60, the genetic correlations were higher in the initial test-day yield and decreased when the test-day interval was increased.…”

Estimation of genetic parameters for body weight traits in Mazandaran native breeder hens by random regression models

“…The structure of records has shown in table 1. Residual variances were modeled via a step function with the following classes: 1, 3 (1-8, 9-12 and 13-32 weeks) (SESANA et al, 2010).…”