Regularized canonical correlation models improve prediction of weather impacts on semen quality in Murciano-Granadina bucks.

This study examined the influence of environmental variables on semen quality in Murciano-Granadina bucks over a 10-year period (2010-2019), analyzing 115 males and 6868 ejaculates. Regularized Canonical Correlation Analysis (rCCA) was applied to overcome multicollinearity and improve prediction of relationships between climatic factors and semen traits. Results showed that bucks displayed resilience to high temperatures, with positive associations between temperature and sperm motility, viability, and morphology. In contrast, cold stress, particularly when combined with strong wind gusts and low barometric pressure, negatively impacted ejaculate volume, motility, and membrane integrity. Rainfall also influenced sperm concentration and acrosome integrity. The first two canonical functions explained over 84% of shared variance, highlighting thermo-biological and atmospheric gradients as key determinants of reproductive performance. These findings demonstrate the utility of rCCA as a predictive tool and underscore the importance of integrating climatic monitoring into artificial insemination programs to enhance semen management, breeding efficiency, and the sustainability of goat production.