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The quantitative assessment of spermatozoa using computer\u2010assisted sperm analysis (CASA) yields valuable kinetic variables that can vary across cattle breeds. This study aimed (i) to classify post\u2010thawed semen samples from Holstein, Simmental and Charolais bulls based on eight CASA\u2010derived variables, progressive motility (PM), non\u2010PM, velocity curve linear (VCL), velocity straight line (VSL), beat\u2010cross frequency (BCF), amplitude of lateral head displacement (ALH), hyperactivity and velocity average path (VAP); (ii) to benchmark three tree\u2010based classifiers, C5.0, random forest (RF) and stochastic gradient boosting (SGB), for their ability to assign ejaculates to the correct breed; and (iii) to identify the most informative predictors for breed discrimination within the algorithms. We applied and compared the predictive performance of three tree\u2010based classification algorithms: C5.0, RF and SGB after the original dataset was randomly divided into the training and testing sets with 70%\u201330%, 75%\u201325% and 80%\u201320% ratios, respectively. Parameter tuning was carried out with the application of a 10\u2010fold cross\u2010validation technique with ten times repetition. The results showed that SGB achieved the highest performance for classification, with a mean balanced accuracy of 85.7% (86.4% for Holstein, 84.3% for Simmental and 86.5% for Charolais), followed by RF (83.5%) and C5.0 (73.5%). PM, hyperactivity and VSL were the most informative predictors. The results offer insights into breed\u2010specific sperm characteristics, with potential implications for the development of breed\u2010specific calibrations for CASA and ensure more efficient resource allocation in livestock production.<\/jats:p>","DOI":"10.1002\/vms3.70539","type":"journal-article","created":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T11:28:58Z","timestamp":1754047738000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Comparison of Tree\u2010Based Machine Learning Algorithms for Classification of Livestock Breeds Based On Post\u2010Thaw Spermatological Parameters"],"prefix":"10.1002","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1943-2690","authenticated-orcid":false,"given":"Do\u011fukan","family":"\u00d6zen","sequence":"first","affiliation":[{"name":"Faculty of Veterinary Medicine Department of Biostatistics Ankara University  Ankara 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P.Shanmugavadivu S.Vijayalakshmi P.Shreyansh andR.Sivaranjani.2024. \u201cEnsemble Learning Algorithm for Cattle Breed Identification Using Computer Vision Techniques.\u201d InProceedings of the 1st International Conference on Artificial Intelligence Communication IoT Data Engineering and Security EAI.https:\/\/doi.org\/10.4108\/eai.23\u201011\u20102023.2343338."},{"key":"e_1_2_9_65_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.anireprosci.2021.106849"},{"key":"e_1_2_9_66_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0378\u20104320(00)00099\u20103"},{"key":"e_1_2_9_67_1","doi-asserted-by":"publisher","DOI":"10.5398\/medpet.2013.36.2.101"}],"container-title":["Veterinary Medicine and Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/vms3.70539","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T12:04:00Z","timestamp":1758715440000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/vms3.70539"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8]]},"references-count":66,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2025,9]]}},"alternative-id":["10.1002\/vms3.70539"],"URL":"https:\/\/doi.org\/10.1002\/vms3.70539","archive":["Portico"],"relation":{},"ISSN":["2053-1095","2053-1095"],"issn-type":[{"type":"print","value":"2053-1095"},{"type":"electronic","value":"2053-1095"}],"subject":[],"published":{"date-parts":[[2025,8]]},"assertion":[{"value":"2025-02-28","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-07-16","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-08-01","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70539"}}