| Autor: |
Atoui, Ahlem, Carabano, Maria Jesus, Tlahig, Samir, Laroussi, Aicha, Abdennebi, Mouldi, Bensalem, Farah, Najari, Sghaier |
| Zdroj: |
Euro-Mediterranean Journal for Environmental Integration; 20240101, Issue: Preprints p1-10, 10p |
| Abstrakt: |
To conceive an applicable genetic improvement plan for local goat population under arid regions, the study aims to determine the genetic parameters of linear body measurements and their correlation with body weight. Additionally, the study analyses statistical models and barymetric functions to predict body weight on the basis of their morphometric data. A random regression model (RRM) was applied to estimate covariance components and genetic parameters for weights and linear body measurements. The data comprised 13,095 records belonging to 945 local kids (progenies of 22 sires and 285 dams) born between 1998 and 2014. Year × month, sex × type of birth, and age of dam at kidding were classified as fixed effects. Random effects included in the model were the direct/maternal additive genetic effect, direct/maternal permanent environmental effect, and residual effect. Direct and maternal heritability estimates of linear body measurements ranged from 0.16 to 0.34 and 0.12 to 0.21, respectively, in which the total length had the lowest direct and highest maternal heritability estimates at birth among the other age groups. A significant maternal effect was obtained in early stage that decreased as the kids advanced in age. A negative correlation was found between direct and maternal additive genetic traits. Estimates of genetic correlations among linear body measurements were high and positive, with values ranging from 0.11 to 0.97, whereas the phenotypic correlation ranged from 0.05 to 0.83. The coefficient of determination for heart girth (R2= 0.88) was higher than other body measurements in single trait evaluation, indicating it as the best trait for the predication of body weight; an increase in the coefficient of determination (R2) was observed as more variables were included in the prediction equation, which indicates more precision in the determination of body weight. These traits could be used as a marker for estimating body weight and for sustainable genetic improvement in local goat population. |
| Databáze: |
Supplemental Index |
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