Genetic parameters for marbling and body score in Anglonubian goats using Bayesian inference via threshold and linear models

Abstract

ObjectiveThe aim of this study was to estimate (co) variance components and genetic parameters for categorical carcass traits using Bayesian inference via mixed linear and threshold animal models in Anglonubian goats.MethodsData were obtained from Anglonubian goats reared in the Brazilian Mid-North region. The traits in study were body condition score, marbling in the rib eye, ribeye area, fat thickness of the sternum, hip height, leg perimeter, and body weight. The numerator relationship matrix contained information from 793 animals. The single- and two-trait analyses were performed to estimate (co) variance components and genetic parameters via linear and threshold animal models. For estimation of genetic parameters, chains with 2 and 4 million cycles were tested. An 1,000,000-cycle initial burn-in was considered with values taken every 250 cycles, in a total of 4,000 samples. Convergence was monitored by Geweke criteria and Monte Carlo error chain.ResultsThreshold model best fits categorical data since it is more efficient to detect genetic variability. In two-trait analysis the contribution of the increase in information and the correlations between traits contributed to increase the estimated values for (co) variance components and heritability, in comparison to single-trait analysis. Heritability estimates for the study traits were from low to moderate magnitude.ConclusionDirect selection of the continuous distribution of traits such as thickness sternal fat and hip height allows obtaining the indirect selection for marbling of ribeye.

Relation between body condition score and conception rate of Japanese Black cows

“…The estimated heritability of CR (0.012 and 0.021) was lower than that reported for Holstein cows (0.027 to 0.049) in Japan [ 30 ]. Low DIC of the model with BCS indicated that the model was better than the model without BCS [ 31 ]. The statistical significance of BCS for CR comfirms that BCS should be included in the genetic analysis of CR records.…”

Bayesian estimates of genetic parameters of non-return rate and success in first insemination in Japanese Black cattle

“…p t e d A r t i c l einterpreted such that the pool of genes affecting the reproductive cycle of an individual and their expression in heifers might be different from that in cows[9].For Bayesian analysis with the use of Gibbs samplings, low values of the Geweke criterion and MCE for NRR and SFI in both heifers and cows indicated that the amount of posteriori of heritability estimates was valid for binary traits. The low value of MCE indicates that the chain size for particular Bayesian analyses is confirmed as reaching convergence[21]. For the two traits in both heifers and cows, narrow interval of CI and small value of DIC indicating that the model is reliable for estimating NRR and SFI.DIC is a parameter for comparing models, being based on posterior distribution of the likelihood ratio[22].The low genetic correlation of traits of heifer with traits of cow may be due to several factors.…”