Abstract

This study reports genetic and environmental (co)variance components for productivity traits of Makooei sheep, using between 2647 and 3418 records obtained from 1429 ewes. Data were collected during 1996–2009 on the Breeding Station of Makooei sheep, located in Makoo in the west-Azerbaijan province of Iran. Genetic parameters were estimated for three basic and six composite traits. The basic traits were conception rate (CR), number of lambs born (NLB) and number of lambs alive at weaning (NLAW). The composite traits were number of lambs born per ewe exposed (NLBEE), number of lambs weaned per ewe exposed (NLWEE), total litter weight at birth per ewe lambed (TLBW), total litter weight at weaning per ewe lambed (TLWW), total litter weight at birth per ewe exposed (TLBWEE) and total litter weight at weaning per ewe exposed (TLWWEE). Genetic parameters were estimated with univariate and bivariate models using restricted maximum likelihood (REML) procedures. Random effects were explored by fitting additive direct genetic effects, permanent environmental effects due to the animal as well as service sire effects in different models for ewe productivity. The most appropriate model for each trait was determined based on likelihood ratio tests and Akaike's Information Criterion (AIC). Direct heritability estimates for CR, NLB, NLAW, NLBEE, NLWEE, TLBW, TLWW, TLBWEE and TLWWEE were 0.05±0.02, 0.11±0.01, 0.06±0.01, 0.08±0.02, 0.04±0.02, 0.17±0.03, 0.12±0.02, 0.13±0.02 and 0.10±0.02, respectively. The estimate for the permanent environmental variance due to the animal ranged from 0.03±0.02 for CR to 0.12±0.01 for NLAW, whereas service sire effects ranged from 0.02±0.01 for TLWW to 0.05±0.01 for TLBW. Genetic correlation estimates among studied traits ranged from −0.13 for CR with TLWW to 0.97 for NLAW with NLWEE. Phenotypic correlation estimates were generally smaller in magnitude than genetic correlations. Service sire effects were found to be important only for litter weight traits. These estimates of genetic parameters may provide a basis for deriving selection indexes for reproductive traits.

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