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Asian Journal of Animal Sciences
Year: 2017  |  Volume: 11  |  Issue: 1  |  Page No.: 23 - 31

Impact of Maternal Components on Ranking of Animal Models in Genetic Parameter Estimation for Daily Gain Traits in Egyptian Rahmani Lambs

Hend A. Radwan and Nazem A. Shalaby    

Abstract: Background and Objective: Average daily gain trait of lambs at different ages has a very important effect on the profitability of sheep production systems. Developments of effective selecting and breeding programs for genetic optimization the growth rate of the lambs require accurate covariance components and genetic parameters estimates. The aim of this study was to estimate variance, covariance components and genetic parameters for average daily gain traits from birth to weaning (ADG0,3), from weaning to 6 months (ADG3,6) and from birth to 6 months age (ADG0,6) in Rahmani sheep flock maintained at El-Serw Experimental Station, over a period of 10 years (1991-2001), show the effect of the including or excluding maternal components during the genetic evaluation of the traits under study, clarify the most appropriate animal model and rank them according to Akaike Information Criterion (AIC). Materials and Methods: Records of growth traits of 5879 lambs, offspring of 1766 ewes and 299 rams were used in the study. Analysis were carried out by 6 single and multi-trait animal models based on including or excluding to maternal components and locating the most appropriate model for the analysis average pre and post-weaning weight gain traits by determining the akiake information criterion and testing the log likelihood values. Results: Since, the log likelihood of the first and second models were non-significant, which indicates the amount of maternal permanent environmental effect was negligible. Conclusion: It could be concluded that the simple model is the best model in designing of breeding programs for average daily gain traits in Rahmani lambs. A modest rate of genetic improvement could be achieved in the flock through selection. Maternal permanent environmental effects contributed 7 and 29% of the total phenotypic variation in ADG0,3 in single and multi-trait analysis, respectively.

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