Estimate of genetic parameters for carcass traits and visual scores in meat sheep using bayesian inference via threshold and linear models

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Abstract

The aim of this study was to estimate the variance components and genetic parameters for marbling in the ribeye area (MRA) and body condition score (BCS) using Bayesian inference via mixed linear and threshold animal models. Data were obtained from Santa Ines breed sheep reared in the Brazilian Mid-North region. Analyses considering the Monte Carlo methods were performed with Markov chains from 500000 cycles onward. A 200000-cycle initial burn-in was considered with values taken at every 250 cycles, in a total of 1200 samples. The Monte Carlo Error deviations were low for the means heritability in all chains by both linear and threshold models. Additive variances estimated by threshold model were higher than those estimated by the linear model. Marble meat from the ribeye area and body condition score can be used as selection criteria to obtain genetic progress in Santa Inês sheep.

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Figueiredo Filho, L. A. S., Sarmento, J. L. R., do Ó, A. O., Santos, N. P. da S., Sena, L. S., & de Sousa Júnior, A. (2017). Estimate of genetic parameters for carcass traits and visual scores in meat sheep using bayesian inference via threshold and linear models. Ciencia Rural, 47(3). https://doi.org/10.1590/0103-8478cr20160174

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