Chen, L., Foxworth, W., Horner, S., Hitit, M., Kidane, N., & Memili, E. (2024). Risk Factor Analysis and Genetic Parameter Estimation for Pre-Weaning Mortality Traits in Boer, Spanish, and Crossbred Goat Kids. Animals, 14, 1085. https://doi.org/10.3390/ani14071085
Chen, L., Foxworth, W., Horner, S., Hitit, M., Kidane, N., & Memili, E. (2024). Risk Factor Analysis and Genetic Parameter Estimation for Pre-Weaning Mortality Traits in Boer, Spanish, and Crossbred Goat Kids. Animals, 14, 1085. https://doi.org/10.3390/ani14071085
Chen, L., Foxworth, W., Horner, S., Hitit, M., Kidane, N., & Memili, E. (2024). Risk Factor Analysis and Genetic Parameter Estimation for Pre-Weaning Mortality Traits in Boer, Spanish, and Crossbred Goat Kids. Animals, 14, 1085. https://doi.org/10.3390/ani14071085
Chen, L., Foxworth, W., Horner, S., Hitit, M., Kidane, N., & Memili, E. (2024). Risk Factor Analysis and Genetic Parameter Estimation for Pre-Weaning Mortality Traits in Boer, Spanish, and Crossbred Goat Kids. Animals, 14, 1085. https://doi.org/10.3390/ani14071085
Abstract
The objectives of this study were to evaluate fixed risk factors associated with PWM and to estimate genetic parameters for PWM. A total of 927 birth records from a mixed population of purebred and crossbred Boer and Spanish goats born between 2016 and 2023 at the International Goat Research Center (IGRC) were used for this study. Four binary traits were studied: D0-3 (death within 3 days after birth), D4-60 (death between 4 and 60 days), D61-90 (death between 61 and 90 days), and D0-90 (death within 90 days). Logistic regression models were used to evaluate the risk factors associated with PWM traits. Bayesian threshold models and Gibbs sampling were used to estimate the genetic parameters. Birth weight, season, litter size, sex, dam age, breed, and heterosis were found to be significantly associated with at least one of the PWM traits. Heritability estimates were 0.263, 0.124, 0.080, and 0.207, for D0-3, D4-60, D61-90, and D0-90, respectively. The genetic correlations between the studied traits ranged from 0.892 (D0-3 and D0-90) to 0.999 (D0-3 and D61-90). These results suggest that PWM in goats is influenced by both non-genetic and genetic factors and can be reduced by management, genetic selection, and crossbreeding approaches.
Biology and Life Sciences, Agricultural Science and Agronomy
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