Structural equation modeling for genetic analysis of body weight traits in Moghani sheep
2021
Jafaroghli, Morteza | Soflaee Shahrbabk, Mohammad | Ghafouri-Kesbi, Farhad | Mokhtari, Morteza
The aim of the present study was to investigate the advantages of structural equation modeling for genetic evaluation of body weight traits in Moghani sheep, using data collected on 6,320 Moghani lambs during a 23-year period (1988 to 2011) in Jafarabad Breeding Station of Moghani Sheep. Traits investigated were the body weight at birth (BW), weaning (WW), six-month (6MW), nine-month (9MW) and yearling weight (YW). Three multivariate animal models including the standard (SMM), fully recursive (FRM) and temporal recursive (TRM) models were compared in terms of deviance information criterion (DIC) and predictive ability measures including mean square of error (MSE) and Pearson's correlation coefficient between the observed and predicted values (r(y, )) of records. Spearman's rank correlation coefficients between posterior means of direct genetic effects for the studied traits were also calculated across all, 50% top-ranked, 10% top-ranked and 1% top-ranked animals. In general, TRM performed better than SMM and FRM in terms of DIC, MSE and r(y, ): resulting in the lowest DIC and MSE and the highest r(y, ). All structural coefficients estimated by TRM were statistically significant. Comparisons of Spearman's rank correlations between posterior means of direct genetic effects of lambs for the studied body weight traits under SMM and TRM showed that considering the causal relationships among the studied growth traits resulted in considerable re-ranking of the animals based on the estimated breeding values, especially for the top-ranked animals; implying that TRM had more plausibility over SMM for genetic evaluation of these traits in Moghani sheep.
Afficher plus [+] Moins [-]Mots clés AGROVOC
Informations bibliographiques
Cette notice bibliographique a été fournie par Shahid Bahonar University of Kerman
Découvrez la collection de ce fournisseur de données dans AGRIS