Genetic analysis of growth parameters and optimum age and weight slaughter prediction in Kurdi sheep

The objective of this study was twofold: first, it aimed at estimating genetic parameters related to growth curve using nonlinear models (Brody, Gompertz, Logistic, Von Bertalanffy, and Richards); secondly identifying an optimum age and weight for both male and female Kurdi sheep breed. To this end, the information related to the pedigree (n = 17,669) due to sires (n = 162) and dams (n = 1968) for body weight traits Viz. birth weight (BW), 3-month-old weight (3 MW), 6-month-old weight (6 MW), 9-month-old weigh (9 MW) and 12-month-old weight (12 MW) were used. To find the best-fitted model, several measures were employed including the Akaike in-formation criterion (AIC), root mean square error (RMSE), coefficient of determination (R2), mean absolute deviation (MAD), and Bayesian information criterion (BIC). The DMU software was employed to determine the growth genetic variance components. Given AIC, MSE, and R2, the Brody model was selected as the best-fitted one for describing the growth curve in the Kurdi sheep breed. The fitted parameters A (estimated mature weight), B (an integration constant related to initial animal weight), and K (maturation rate) were estimated for models by sex separately. However, since Brody does not have a turning point to determine the appropriate turning point, we used the results of the second best-fitted model, viz Von Bertalanffy model, to find the optimum age and weight slaughter in Balafrej, (2019) equations. According to the results, there was a greater variance in weight between males and females at 12 MW compared to other ages. The optimal slaughter weights for males and females were 28.14 and 22.44 kg, respectively, and the corresponding ages were 120.49 and 90.31 days. By utilizing a multivariate animal model, the prediction of heritability for parameters A, B, and K was calculated to be 0.055, 0.117, and 0.012 respectively; indicating that genetic variation is relatively insignificant in these growth parameters. Further analysis revealed negative genetic correlations between growth parameters at rates of -0.200 (A-B), -0.471 (A-K), and, -0.220 (B-K). The prediction of genetic trends for A, B, and K parameters was obtained as 0.043, 0.043, and 0.001gr/yr which could reflect different modes of selection pressure over these parameters. Despite not being the best-fitted model for Kurdi growth data, the Von Bertalanffy model can still be utilized to predict the live weight of the Kurdi sheep breed. Nonetheless, for genetic-based decision--making aimed at picking out superior animals based on accurate growth parameter predictions, it is recommended that findings from the Brody model be adapted for downstream genetic analysis in the Kurdi sheep breed.