Pilot evaluation of sperm mobility for boar fertility classification using machine learning

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 n = 11; <75%, LCR n = 10) were shipped overnight on day of collection, stored at 17 °C, and analyzed for mobility and CASA parameters across three weekly replicates. Across all boars, mobility was associated with CR (r = 0.47; P = 0.03) and moderately predictive of fertility group using binomial logistic regression (AUC = 0.77; P < 0.01), correctly ranking boars by CR group 77% of the time. Including stud as an interaction improved ranking to 83% (AUC = 0.83; P < 0.01), though model improvement was not significant. A random forest algorithm using CASA parameters and mobility reduced the model's classification error compared to CASA alone following feature selection (28.6% vs 22.4%), but an AUC of 1.00 indicates overfitting and the need for more boars to confirm this finding. Mobility was also found to be reflective of kinematics (P < 0.05) including Amplitude of Lateral Head Displacement (ALH; r = -0.57) and Linearity (LIN; r = 0.53). Sperm Wobble (WOB) was the only significant parameter for both CR (r = 0.45) and mobility (r = 0.46). Because sperm kinematics reflect underlying flagellar function and membrane physiology, mobility may also have utility as a broader indicator of semen quality, though further validation is needed. While mobility values were associated with CR and improved classification when combined with CASA parameters, these models are preliminary and reflect proof-of-concept rather than finalized predictive tools. Validation in larger and more genetically diverse populations is essential before routine application in commercial settings.