Genetic Assessment of Fitness in Beetal Goats

Background: The present study aimed to evaluate the fitness of Beetal goats through a combination of logistic regression and Bayesian statistical approaches using data from the Directorate of Livestock Farms, GADVASU, Ludhiana. Methods: Fitness classification based on mortality records and non-genetic factors such as sex, season and year of birth from 2015 to 2023 were extracted from records at the Directorate of Livestock Farms, GADVASU. A total of 530 animal records belonging to 230 dam families sired by 52 males were used, out of which 230 death records were reported and 466 animals survived upto one year of age. Result: Logistic regression analysis revealed that all three variables significantly influenced survival, with female goats and those born in cooler seasons showing higher odds of being classified as high-fitness. Bayesian analysis was subsequently performed on the filtered dataset using the BLUPF90 suite to estimate additive genetic variance and heritability. The estimated heritability of 0.1791 indicated a modest genetic basis for fitness, with environmental factors contributing the majority of variance. These findings underscore the complex, multifactorial nature of fitness in goats, providing insights for sustainable breeding strategies that enhance health resilience without compromising adaptability. The study also identifies specific years and seasons that influence survivability trends, offering practical implications for livestock management and genetic selection programs.