ArticleTranslational animal science2026
Pilot evaluation of sperm mobility for boar fertility classification using machine learning.
Article in Translational animal science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Predicting boar fertility remains a critical challenge for the swine industry, as standard semen quality measures such as motility and morphology do not accurately predict conception outcomes. This lack of accurate tools allows subfertile boars to enter breeding programs, reducing reproductive efficiency and causing economic loss. Therefore, there is a critical need for practical, readily deployable assays that complement current semen quality assessments and improve fertility prediction. The sperm mobility assay, originally developed for poultry fertility selection, was validated in boars by Vizcarra and Ford (2006), but its relationship to fertility outcomes has not been evaluated. This pilot study evaluated the predictive potential of the mobility assay to classify boars by conception rate (CR) group. Breeding doses from 21 commercial Duroc boars with known CR (>80%, HCR
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