ESTIMATION OF GENETIC TRENDS IN SOME PRODUCTIVE TRAITS OF A ZARAIBI GOAT FLOCK USING QUANTITATIVE AND MOLECULAR GENETIC METHODS

Abstract

This study was carried out to evaluate the breeding plan implemented on Zaraibi goat flock, raised in El-Serw Experimental Farm belongs to the Animal Production Research Institute. Phenotypic selection was practiced since the original flock was entered to the farm in 1984 and starting from the year 2004 the animal breeding values were estimated and taken in consideration along the phenotypic criteria in selecting the animal for breeding. Data on 13062 Zaraibi kids progeny of 253 sires and 2443 dams during 1988 to 2018 were used. A total of 1559 Zaraibi does records at the first lactation during the period from 1990 to 2014 were used to study total milk yield trait. Data were analyzed using two statistical models. The first was used to estimate the non-genetic fixed effects (gender, type of birth, parity and year –season of birth and some interaction between those effects) on body weights at 4, 6 and 12 months of age. The fixed effects for total milk yield were litter size, age of doe and season and year of kidding. Overall least squares mean of the 4, 6 and 12 months weight of Zaraibi goat were estimated as 12.14, 15.49 and 24.08 kg, respectively. Gender and type of birth of kid, parity of dam and year-season of birth affected (p<0.0001) all studied traits. Interaction between gender and type of birth and that between gender and season of birth had non-significant effect on the studied traits. While the interaction between parity of dam and season of birth had a significant effect on body weight at 120 (M4), 180 (M6) and 360 (M12) days of age. The second model included the fixed effects in the first model in addition to the random effect of animal that used for estimating, genetic parameters and the breeding values for estimatly the genetic trend and year constants for the environmental trend for growth traits. A multi-trait animal model program (MTDFREML) of Boldman et al. (1995) was utilized to estimate the breeding values with Best Linear Unbiased Prediction (BLUP) methodology.