The current study aimed to estimate (co)variance components and heritability for pre-weaning body weight traits and Kleiber ratio in Sangsari sheep. Data used in this research were collected over 30 years (1986–2016) at the breeding station of Sangsari sheep. Traits considered were birth weight (BW), weaning weight (WW), pre-weaning daily gain (PWDG), and Kleiber ratio (KR). Genetic parameters were estimated by the average information restricted maximum likelihood (AI-REML) procedure, using six animal models. The most suitable model was selected using the Akaike information criterion (AIC) for each trait. Direct heritability estimates for BW, WW, PWDG and KR were 0.30 $\pm$ 0.04, 0.20 $\pm$ 0.03, 0.15 $\pm$ 0.02, and 0.13 $\pm$ 0.05, respectively. Maternal heritability estimates varied from 0.06 $\pm$ 0.02 for PWDG to 0.12 $\pm$ 0.03 for BW. The maternal permanent environmental effects for the traits of KR, WW and PWDG account for about 7%, 9% and 12% of the phenotypic variance. The estimates of the direct genetic ( ${\mathrm{r}}_{\mathrm{a}}$) and maternal genetic ( ${\mathrm{r}}_{\mathrm{m}}$) correlations among pre-weaning growth traits were positive and ranged from 0.21 (BW-KR) to 0.98 (WW-PWDG) and 0.27 (WW-PWDG) to 0.48 (BW-WW), respectively. Therefore, to have an accurate genetic evaluation, maternal effects need to be considered in any program aimed at improving pre-weaning growth traits. In addition, due to the existence of genetic variation for early growth traits and generally positive and medium to high genetic correlations among them, it can be concluded that in the Sangsari breed of sheep, genetic progress for these traits is possible by selection.

Dairy goat production plays a vital role in meeting nutritional needs and supporting rural livelihoods. This study estimated variance components and genetic parameters for daily milk yield (DMY), daily milk fat yield (DMFY), and daily milk protein yield (DMPY) in Murciano-Granadina goats. The study used data collected from 2015 to 2021 in Ghaleh-Ganj dairy goat farm in Kerman province, Iran. R software was used to evaluate environmental effects, examine genetic and phenotypic trends, and determine genetic-phenotypic correlations. The best model was determined based on Akaike's Information Criterion. (Co)variance components and heritability were estimated using the AIREMLF90 software. For DMY, DMFY, and DMPY, the estimated heritability was 0.21 ± 0.02, 0.13 ± 0.01, and 0.17 ± 0.02, respectively. The repeatability estimates were moderate, ranging from 0.40 for DMPY to 0.46 for DMY. The contribution of animal permanent environmental effect to the total phenotypic variance was estimated as 21, 48, and 17% for DMY, DMFY, and DMPY, respectively. The estimates of genetic correlations between DMY-DMFY, DMY-DMPY, and DMFY-DMPY were 0.62 ± 0.0140, 0.67 ± 0.010, and 0.85 ± 0.009, respectively. Estimates of phenotypic correlations among traits ranged from -0.12 ± 0.006 for DMY-DMFY and DMY-DMPY to 0.35 ± 0.005 for DMFY-DMPY. This investigation revealed moderate heritability and positive and moderate genetic correlations among the observed dairy traits. These results can be used to establish a breeding plan to improve the production level of Murciano-Granadina goats.

Using Kermani sheep, the current study estimated (co)variance components and genetic parameters for average daily gain, Kleiber ratio, growth efficiency and relative growth rate. Data were analyzed by the average information restricted maximum likelihood (AI-REML) method using six animal models with different combinations of direct and maternal effects. The best-fitting model was determined after testing for improvement in log-likelihood values. The estimates of h2 for average daily gain (ADG), Klieber ratio (KR), growth efficiency (GE) and relative growth rate (RGR) in pre- and post-weaning phases were 0.13 ± 0.6 and 0.17 ± 0.02, 0.12 ± 0.04, and 0.16 ± 0.03; 0.05 ± 0.05 and 0.07 ± 0.03 and 0.06 ± 0.02 and 0.07 ± 0.01, respectively. Maternal heritabilities (m²) ranged from 0.03 ± 0.01 for relative growth rate in pre-weaning phase to 0.11 ± 0.04 for average daily gain in post-weaning period. The maternal permanent environmental component (Pe²) accounted for 3–13% to the phenotypic variance for all the studied traits. Estimated values of additive coefficient of variations (CV_A) ranged from 2.79% for relative growth rate at six months of age to 23.74% for growth efficiency at yearling age. Genetic and phenotypic correlations among traits were ranged from − 0.687 to 0.946 and − 0.648 to 0.918, respectively. The result indicated that selection for growth rate and efficiency-related traits would also be less effective in achieving genetic change, because there was little additive genetic variation among Kermani lambs.