Revista Brasileira de Zootecnia
On-line version ISSN 1806-9290
DORNELLES, Mariana de Almeida et al. Genetic parameters and genetic and phenotypic trends of performance traits of equines from the Brazilian Army. R. Bras. Zootec. [online]. 2012, vol.41, n.6, pp. 1419-1425. ISSN 1806-9290. http://dx.doi.org/10.1590/S1516-35982012000600015.
The objective of this research was to compare the magnitude of genetic parameters (coefficients of heritability and genetic correlation) as estimated by the Restricted Maximum Likelihood (REML) method and Bayesian Inference, and to estimate the genetic and phenotypic trends to the traits height at the withers (HW24) and weight at 24 months of age (W24). The average heritability estimated by Bayesian Inference to HW24 was 0.47, and it was lower than that obtained by REML bi-trait analysis (0.52); however, the value estimated to W24 (0.39) was higher than that obtained by REML bi-trait analysis (0.38). The genetic correlation estimate between W24 and HW24 traits obtained by the REML method (0.66) was lower than that obtained by the Bayesian Inference Method (0.72). From the regression of the average additive genetic merit in the year of birth of the animals, it was found that the averaged genetic values of the animals for HW24 showed a genetic trend near zero (-0.0008cm/year), and the averaged genetic values for W24 showed a negative trend of -0.38 kg/year. The values to the direct heritability estimated for HW24 and W24 suggest that the direct selection for these traits can provide genetic gain in this population. The genetic correlation between the traits, high and positive, suggests that the selection for HW24 should promote increase in W24 at this age. The genetic trends obtained for the traits studied, near zero, indicate that the selection performed produced a slight reduction of the weight of the animals at 24 months of age; however, it did not promote increase in height at the wither at this same age, in this population.
Keywords : genetic correlation; genetic progress; variance components.