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Background <p>Artificial insemination (AI) success in Murciano-Granadina goats is influenced by a complex interaction of male, female, management, and environmental factors. This study aimed to identify the main drivers and threshold conditions affecting fertility outcomes in commercial AI programs using long-term field data.</p> Results <p>A dataset of 3,122 inseminations performed between 2010 and 2019 was analyzed using canonical discriminant analysis and CHAID decision trees. Multicollinearity screening excluded 24 redundant predictors out of an initial set of 52 variables, retaining 28 variables with the greatest explanatory power. The canonical model showed that the first six functions explained 72.4% of total variance, with barometric pressure, temperature, and rainfall at insemination as dominant environmental loadings. Fertility increased when minimum temperatures exceeded 14.7&#xa0;°C but declined below 9&#xa0;°C, coinciding with reduced semen quality. Wind speeds above 2.9&#xa0;m/s and humid easterly winds reduced conception probability by up to 18% due to potential stress-inducing effects at semen collection. Altitudes between 451 and 720&#xa0;m were associated with the highest fertility rates. Management thresholds were also important: fertility declined when inseminated group size exceeded 63 does, whereas herds larger than 50 animals showed improved synchrony and higher conception probabilities. Female age strongly influenced outcomes, with immature does (~ 2&#xa0;years) more frequently associated with low fertility, while multiparous females (&gt; 3 parturitions) achieved fertility rates up to 15% higher. Bucks aged 3–5&#xa0;years produced semen with superior fertility outcomes compared with younger (1–3&#xa0;years) or older (&gt; 7&#xa0;years) males. Somatic cell counts below 3,000 × 10<sup>3</sup>/mL increased the probability of high fertility outcomes, whereas counts above 4,000 × 10<sup>3</sup>/mL were associated with markedly reduced success. Compensatory outcomes were also observed, where acceptable fertility occurred despite low semen quality under favorable physiological and management conditions.</p> Conclusions <p>AI fertility in Murciano-Granadina goats results from multifactorial interactions among environmental conditions, physiological status, and herd management. Identifying key environmental, physiological, and management thresholds may contribute to improved planning of AI programs and may help guide future strategies aimed at enhancing reproductive efficiency.</p>

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Drivers of artificial insemination fertility in Murciano-Granadina goats: a ten-year multifactorial approach integrating buck–doe interactions across physiological, environmental, and management conditions

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月16日

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  • María Pía Peláez Caro,
  • Ander Arando Arbulu,
  • José Manuel León Jurado,
  • Juan Vicente Delgado Bermejo,
  • Javier Fernández Álvarez,
  • Francisco Javier Navas González

摘要

Background

Artificial insemination (AI) success in Murciano-Granadina goats is influenced by a complex interaction of male, female, management, and environmental factors. This study aimed to identify the main drivers and threshold conditions affecting fertility outcomes in commercial AI programs using long-term field data.

Results

A dataset of 3,122 inseminations performed between 2010 and 2019 was analyzed using canonical discriminant analysis and CHAID decision trees. Multicollinearity screening excluded 24 redundant predictors out of an initial set of 52 variables, retaining 28 variables with the greatest explanatory power. The canonical model showed that the first six functions explained 72.4% of total variance, with barometric pressure, temperature, and rainfall at insemination as dominant environmental loadings. Fertility increased when minimum temperatures exceeded 14.7 °C but declined below 9 °C, coinciding with reduced semen quality. Wind speeds above 2.9 m/s and humid easterly winds reduced conception probability by up to 18% due to potential stress-inducing effects at semen collection. Altitudes between 451 and 720 m were associated with the highest fertility rates. Management thresholds were also important: fertility declined when inseminated group size exceeded 63 does, whereas herds larger than 50 animals showed improved synchrony and higher conception probabilities. Female age strongly influenced outcomes, with immature does (~ 2 years) more frequently associated with low fertility, while multiparous females (> 3 parturitions) achieved fertility rates up to 15% higher. Bucks aged 3–5 years produced semen with superior fertility outcomes compared with younger (1–3 years) or older (> 7 years) males. Somatic cell counts below 3,000 × 103/mL increased the probability of high fertility outcomes, whereas counts above 4,000 × 103/mL were associated with markedly reduced success. Compensatory outcomes were also observed, where acceptable fertility occurred despite low semen quality under favorable physiological and management conditions.

Conclusions

AI fertility in Murciano-Granadina goats results from multifactorial interactions among environmental conditions, physiological status, and herd management. Identifying key environmental, physiological, and management thresholds may contribute to improved planning of AI programs and may help guide future strategies aimed at enhancing reproductive efficiency.