Estimation of (Co) variance components and genetic parameters for growth traits in Lori-Bakhtiarilambs using a Bayesian approach via Gibbs sampling

The object of this study was to estimate (co)variance components and genetic and environmental parameters for body weights at different ages in Lori-Bakhtiari sheep using a Bayesian approach.In this study, pedigree information and birth weight, one month weight, weaning weight, 6 month weight, 9 months weight and 12 months weight, of 7697 lambs from the 291 rams and 2097 ewes were used. The data was collected in Shahrekord sheep breeding station (sholi) during 1989- 2011. The SAS statistical software was used to determine the effect of environmental factors, and MTGSAM software via Gibbs sampling was applied to estimate genetic parameters. Environmental factors like birth year, sex, type of birth and age of mother on lambing timehad significant effect on traits, which included in the model as fix effects. Animal’s age at weighting day was introduced to the model as covariate. Using best chosen model, the direct heritability for birth weight, one-month, weaning weight, 6 months weight, 9 months weight and 12 months weight were respectively obtained as follows: 0.33±0.03, 0.11±0.02, 0.15±0.02, 0.23±0.02, 0.29±0.03 and 0.38±0.03. Gibbs sampling in Bayesian statistical analysis could provide reasonable range expected estimations for parameters. The results showed that growth traits more are influenced by mother’s genetic factors in the early of age. With increasing age, due to decreases dependence to her mother, the significance of this effect is reduced. The lower to moderate estimates of direct heritabilityfor growth at different ages, obtained in this survey indicate that selection for these traits will be lead to lower to moderate genetic improvement.