Genetic variability of body weight in two goose strains under long-term selection.

Body weight is one of the most important traits in any genetic improvement program in geese for at least 2 reasons. First, measurements of the trait are very easy. Second, body weight is correlated with a number of other meat performance traits. However, the genetic background of body weight shows considerable complexity. Three genetic models (with direct, maternal genetic and permanent maternal environmental effects) were employed in this study. Records of 3076 individuals of maternal strain W11 and 2656 individuals of paternal strain W33 over 6 consecutive generations, kept in the pedigree farm of Koluda Wielka, were analysed. Body weight (in kilograms) was measured in weeks 8 (BW8) and 11 (BW11). The inbreeding levels in both populations were relatively low (0.14% and 0.02% for W11 and W33, respectively), therefore these effects were not included in the linear models to estimate genetic parameters. Three fixed effects (hatch period, sex and year) were included in each linear model. Two criteria (AIC, BIC) were used to check the goodness of fit of the models. The computations were performed by WOMBAT software. In general, the genetic parameter estimates varied across the traits, models and strains studied. Direct additive heritability estimates ranged from 0.0001 (for BW11 of W33) to 0.55 (for BW11 of W33). Maternal and total heritabilities were also variable. Estimates of ratios of direct-maternal effect covariance in phenotypic variance were both positive and negative, but they were negligible, whereas ratios of the permanent environmental maternal variance to phenotypic variance were close to zero. Both of the applied criteria of model adequacy indicate that the model with maternal genetic and environmental effects should be considered as optimal. Genetic trends were close to zero. It seems that they were influenced by long-term selection. Similar tendencies have been observed for phenotypic trends, as well.

Curvilinear inbreeding effects on some performance traits in laying hens.

Quadratic partial regression coefficients were estimated for the inbreeding level on five performance traits (body weight, average egg weight, age at first egg, percentage of fertilized eggs, and hatchability of set eggs) of two strains of laying hens. Data on 5631 of H77 layers and 3563 of N88 layers from nine consecutive generations were analysed. Only dams were accounted for. Partial regression coefficients were estimated by REML with a single-trait animal model, which included fixed effects (generation and hatching period) and random effects (additive genetic and error effects). The mean inbreeding level was 0.87% in strain H77 and 1.08% in strain N88. The inbreeding effects were analysed based on the quadratic partial regression equations. A slight inbreeding depression was found for all the traits analysed in N88. In strain H77, negative effects of inbreeding were only noted for body weight and average egg weight. The small inbreeding effects shown here resulted from a relatively low level of homozygosity in the populations studied. The strains were found to differ in the effects of inbreeding. It is worth pointing out that differences were noted both between the inbreeding depression estimated from the partial linear regression equation and the quadratic partial regression equation, as well as different inbreeding levels.