1. A study was conducted to study direct dominance genetic and maternal effects on genetic evaluation of production traits in dual-purpose chickens. The data set consisted of records of body weight and egg production of 49 749 Mazandaran fowls from 19 consecutive generations. Based on combinations of different random effects, including direct additive and dominance genetic and maternal additive genetic and environmental effects, 8 different models were compared. 2. Inclusion of a maternal genetic effect in the models noticeably improved goodness of fit for all traits. Direct dominance genetic effect did not have noticeable effects on goodness of fit but simultaneous inclusion of both direct dominance and maternal additive genetic effects improved fitting criteria and accuracies of genetic parameter estimates for hatching body weight and egg production traits. 3. Estimates of heritability (h) for body weights at hatch, 8 weeks and 12 weeks of age (BW0, BW8 and BW12, respectively), age at sexual maturity (ASM), average egg weights at 28-32 weeks of laying period (AEW), egg number (EN) and egg production intensity (EI) were 0.08, 0.21, 0.22, 0.22, 0.21, 0.09 and 0.10, respectively. For BW0, BW8, BW12, ASM, AEW, EN and EI, proportion of dominance genetic to total phenotypic variance (d) were 0.06, 0.08, 0.01, 0.06, 0.06, 0.08 and 0.07 and maternal heritability estimates (m) were 0.05, 0.04, 0.03, 0.13, 0.21, 0.07 and 0.03, respectively. Negligible coefficients of maternal environmental effect (c) from 0.01 to 0.08 were estimated for all traits, other than BW0, which had an estimate of 0.30. 4. Breeding values (BVs) estimated for body weights at early ages (BW0 and BW8) were considerably affected by components of the models, but almost similar BVs were estimated by different models for higher age body weight (BW12) and egg production traits (ASM, AEW, EN and EI). Generally, it could be concluded that inclusion of maternal effects (both genetic and environmental) and, to a lesser extent, direct dominance genetic effect would improve the accuracy of genetic evaluation for early age body weights in dual-purpose chickens.

In the case of camels, there is little data in the literature on the relationship between body building features and the evaluation of milk yield. In the last decade, a rising interest in camel milk has been observed due to its nutritional and health-promoting properties, resulting in a growing market demand. Despite the remarkable importance of camels, very little improvement in camel breeding and selection for dairy purposes has been achieved. The current study aimed to provide a practical approach to the evaluation of dairy dromedaries based on test day milk and morphometric records. A total of 62 Sindi dairy camels were evaluated and 4176 daily milk records were registered in February, March, April, and May 2021. She-camels were milked twice per day (at morning and evening) by hand before calf sucking. The farming system was intensive with two times feeding. Three measurements had the highest scores in assessing: udder, teats distance and placement, and teats size, which included 45 out of 100 scores. Test day milk records were analysed using a simple repeatability model with two random effects. The range of daily milk yields was estimated between 0.1 to 8.70 kg. The mean of body scores was 77.19 (CI = 74.19–80.19). Daily milk yields moderately correlated with body score (r = +0.27). Additionally, udder circumference and abdomen girth were correlated to milk production. Using test day milk records in breeding programs can be appropriate for the selection and replacement of she-camels, but due to difficulties in accessing these data, using morphometric data is a good criterion for the evaluation of dromedaries in extensive systems.

1. The aim of the present study was to compare different models to estimate variance components for egg weight (EW) in laying hens. 2. The data set included 67 542 EW records of 18 245 Mazandaran hens at 24, 28, 30, 32 and 84 weeks of age, during 19 consecutive generations. Variance components were estimated using multi-trait, repeatability, fixed regression and random regression models (MTM, RM, FRM and RRM, respectively) by Average Information-Restricted Maximum Likelihood algorithm (AI-REML). The models were compared based on Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). 3. The MTM was the best model followed by the Legendre RRMs. A RRM with 2nd degree of fit for fixed regression and 3(rd) and 2(nd) degrees of fit for random regressions of direct additive genetic and permanent environmental effects, respectively, was the best RRM. The FRM and RM were not proper models to fit the data. However, nesting curves within contemporary groups improved the fit of FRM. 4. Heritability estimates for EW by MTM (0.06-0.41) were close to the estimates obtained by the best RRM (0.09-0.45). In both MTM and RRM, positive genetic correlations were estimated for EW records at different ages, with higher correlations for adjacent records. 5. The results suggest that MTM is the best model for EW data, at least when the records are taken at relatively few age points. Though selection based on EW at higher ages might be more precise, 30 or 32 weeks of age could be considered as the most appropriate time points for selection on EW to maximise genetic improvement per time unit.