فهرست نشریات علمی دسترسی آزاد ایران

In the present study, 7,089 test-day records on milk somatic cell counts (SCC) belonging to 2,432 first-parity Murciana-Granadina does in Kerman province were used. Test-day SCC records were transformed into milk somatic cell scores (SCS) and analyzed by applying random regression models (RRM) with the Legendre polynomials (LEG) function with order of 2 to 5 for additive genetic and permanent environmental effects and heterogeneous residual variances. The models were compared using the Akaike's information (AIC) and Bayesian information (BIC) criteria. The model with orders 3 and 2 for additive genetic and permanent environmental effects (RRM-LEG32), respectively, was the best for genetic analysis of test-day SCS. The estimates of heritability (  and the ratio of permanent environmental variance to phenotypic variance ( ) for test-day SCS using the RRM-LEG32 were low. They ranged from 0.03 at days in milk (DIM) 155 and 215 to 0.11 at DIM 35 for  and from 0.01 at DIM 65 to 0.14 at DIM 275 for  estimates. Genetic correlation estimates among test-day SCS at 5, 70, 137, 203, and 275 DIM were lower than the corresponding phenotypic correlations. Genetic correlation estimates ranged from 0.36 between DIM 137 and DIM 275 to 0.97 between DIM 70 and DIM 137 while the phenotypic correlations ranged from 0.03 between DIM 70 and DIM 203 to 0.09 between DIM 5 and DIM 203. In general, the strongest genetic correlations were found between closely located DIMs, with these correlations decreasing as the interval between DIMs increased. The low heritability estimates for test-day SCS records implied that they are mainly controlled by the non-additive genetic and environmental effects, limiting the efficiency of direct genetic selection for improving the test-day SCS. Therefore, including these effects in designing an appropriate breeding program for improvement in Murciano-Granadina goat udder health is of great importance.