Estimates of genetic parameters for total milk yield over multiple ages in Brazilian Murrah buffaloes using different models

Abstract

ABSTRACT. The objective of this study was to estimate variance components and genetic parameters for accumulated 305-day milk yield (MY305) over multiple ages, from 24 to 120 months of age, applying random regression (RRM), repeatability (REP) and multi-trait (MT) models. A total of 4472 lactation records from 1882 buffaloes of the Murrah breed were utilized. The contemporary group (herd-yearcalving season) and number of milkings (two levels) were considered as fixed effects in all models. For REP and RRM, additive genetic, permanent environmental and residual effects were included as random effects. MT considered the same random effects as did REP and RRM with the exception of permanent environmental effect. Residual variances were modeled by a step function with 1, 4, and 6 classes. The heritabilities estimated with RRM increased with age, ranging from 0.19 to 0.34, and were slightly higher than that obtained with the REP model. For the MT model, heritability estimates ranged from 0.20 (37 months of age) to 0.32 (94 months of age). The genetic correlation estimates for MY305 obtained by RRM (L23.res4) and MT models were very similar, and varied from 0.77 to 0.99 and from 0.77 to 0.99, respectively. The rank correlation between breeding values for MY305 at different ages predicted by REP, MT, and RRM were high. It seems that a linear and quadratic Legendre polynomial to model the additive genetic and animal permanent environmental effects, respectively, may be sufficient to explain more parsimoniously the changes in MY305 genetic variation with age.

Application of random regression models for genetic analysis of 305-d milk yield over different lactations of Iranian Holsteins

“…Random regression has been used in most studies to model the additive and permanent environmental effects with homogenous or heterogeneous residual effect [ 1 ]. RRM allows changes in variance along the trajectory and provides the accurate estimation of breeding value compare to repeatability and multiple trait models [ 2 ]. The Mean trend of milk yield or 305-day total yield can be modeled with different orders of orthogonal Legendre polynomial because Legendre polynomial produces the lower correlation between parameters than other functions [ 3 ].…”

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

“…In Iran, the genetic analyses for milk yield of buffalo are carried out using a finite dimensional model, as described in other studies (Rosati & Van Vleck, 2002). However, worldwide, RRM are currently being used for national genetic evaluations of dairy cattle in several countries, such as the United States, Canada, Australia, and Brazil (Sesana et al, 2014). Therefore, it is crucial to apply these models in a genetic evaluation program for milking buffalo in Iran.…”

Genetic evaluation of milking buffaloes (Bubalus bubalis): bull ranking

“…These values can be considered high, indicating that this trait was influenced by genetic factors and therefore should respond well to selection. In the literature values ranging from 0.14 to 0.29 were observed (Tonhati et al, 2004;Ghaffar et al, 2007;Malhado et al, 2009;Rodrigues et al, 2010;Bezerra Jr. et al, 2014;Sesana et al, 2014), being of medium magnitude. In other studies, Campos et al (2007) found a heritability of 0.26 for cumulative production on 305 days of lactation using dairy buffaloes in 13 farms in São Paulo State.…”