Proposal for a method of analyzing sperm subpopulations in bulls
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Elsevier
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This study compared the automatic sperm classification generated by computer-assisted semen analysis (CASA) with a multivariate clustering approach (k-means). Both methods identified 3 sperm subpopulations with distinct motility profiles. However, the k-means clustering method provided clearer group definitions and reduced overlap between subpopulations, suggesting that multivariate methods offer a more detailed characterization of sperm heterogeneity than the automatic CASA classification.
