Early-life growth performance and litter characteristics predict gilt selection and first mating success under commercial conditions

Early-life growth performance and litter characteristics predict gilt selection and first mating success under commercial conditions | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Early-life growth performance and litter characteristics predict gilt selection and first mating success under commercial conditions Sara Crespo, Joaquín Gadea This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9148333/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Background: Efficient gilt replacement is critical for productivity and sustainability in commercial swine systems. Early-life growth and litter characteristics may influence the likelihood of females progressing through key developmental stages; however, their combined predictive value under commercial conditions remains insufficiently characterised. This study evaluated whether early growth performance and litter-level traits predict progression to the transition phase and attainment of first mating using conventional and machine learning approaches. Methods: A total of 510 female piglets from 77 litters sired by eight boars of the same genetic line were monitored from birth to approximately 220 days of age under commercial farm conditions. Recorded variables included birth weight, transition weight (40–46 days), body weight at ~220 days, and average daily gain (ADG) across growth intervals. Litter characteristics comprised total born, number born alive, number born dead, female proportion, and selection ratio. Variance components attributable to sire and dam were estimated using linear mixed-effects models. Progression to transition (n = 346/520) and attainment of first mating (n = 346 monitored) were analysed using logistic regression and Random Forest models with stratified 10-fold cross-validation. Results: Birth weight was positively correlated with transition weight (r = 0.51, p < 0.01) and early ADG (r = 0.34, p < 0.01), but showed weaker associations with body weight at 220 days (r = 0.17, p < 0.01). Litter size negatively affected birth weight (r = –0.29, p < 0.01) but was not associated with weight at 220 days. Maternal effects accounted for 39.9% of birth weight variance, declining to 10.5% at 220 days, whereas paternal variance remained below 3% across traits (h² = 0.006–0.13). Logistic regression identified birth weight as the strongest predictor of transition (OR = 1.66 per additional kg). Random Forest models demonstrated moderate discriminative ability for transition (AUC = 0.77) and first mating (AUC = 0.74), with early ADG emerging as the most influential predictor of first mating attainment. Conclusions: Early-life growth performance, particularly birth weight and pre-transition ADG, significantly influences gilt developmental progression under commercial conditions. Maternal and litter-level effects explain a substantial proportion of early growth variability. The integration of machine learning approaches improves individual-level prediction beyond traditional regression models and supports data-driven gilt selection strategies aimed at enhancing reproductive efficiency and herd sustainability. gilt development early growth litter effects replacement efficiency predictive modelling commercial pig production Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 27 Apr, 2026 Reviewers agreed at journal 19 Mar, 2026 Reviewers invited by journal 19 Mar, 2026 Editor assigned by journal 19 Mar, 2026 Submission checks completed at journal 19 Mar, 2026 First submitted to journal 17 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9148333","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":610528728,"identity":"606ed788-a27a-4332-8e86-878198feca5f","order_by":0,"name":"Sara Crespo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYJADxgcMDHKkaWE2YGAwJk0LmwRRWuTbzz78wFBzT05+dvOxih8VBonz2w8wfviYg1uLwZl0YwmGY8XGBneOpd3sOWOQuOFMArPkzG14tDCkMUgwNiQkbpDIMbvN2PYncQNDAhszLx4t8v3PmH8AtdTPn5FjVsz4D+iw/gf4tTDcSGMD2ZLAcCPHjJmxwSCx4QYBWwxuPGOzSDiWYLjhzrFkyZ5jBsYbbjxsxusX+f405hsfahLkgSF28MOPGgPZ+f3JBz98xOcwEEgAERJwLmMDAfUwIEFYySgYBaNgFIxQAAA1mVAF32PDSAAAAABJRU5ErkJggg==","orcid":"","institution":"CEFUSA","correspondingAuthor":true,"prefix":"","firstName":"Sara","middleName":"","lastName":"Crespo","suffix":""},{"id":610528729,"identity":"c0c3e1db-1744-4937-8eb8-41b768c11905","order_by":1,"name":"Joaquín Gadea","email":"","orcid":"","institution":"University of Murcia","correspondingAuthor":false,"prefix":"","firstName":"Joaquín","middleName":"","lastName":"Gadea","suffix":""}],"badges":[],"createdAt":"2026-03-17 11:38:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9148333/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9148333/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105256003,"identity":"f63faa92-17f1-4423-b482-46013c030b58","added_by":"auto","created_at":"2026-03-24 04:41:49","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":572915,"visible":true,"origin":"","legend":"","description":"","filename":"article1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9148333/v1_covered_86831321-99c3-4fc0-8340-f40b48f2e887.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Early-life growth performance and litter characteristics predict gilt selection and first mating success under commercial conditions","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"porcine-health-management","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"phmj","sideBox":"Learn more about [Porcine Health Management](http://porcinehealthmanagement.biomedcentral.com/)","snPcode":"40813","submissionUrl":"https://submission.nature.com/new-submission/40813/3","title":"Porcine Health Management","twitterHandle":"@animalplantsci","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"gilt development, early growth, litter effects, replacement efficiency, predictive modelling, commercial pig production","lastPublishedDoi":"10.21203/rs.3.rs-9148333/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9148333/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eEfficient gilt replacement is critical for productivity and sustainability in commercial swine systems. Early-life growth and litter characteristics may influence the likelihood of females progressing through key developmental stages; however, their combined predictive value under commercial conditions remains insufficiently characterised. This study evaluated whether early growth performance and litter-level traits predict progression to the transition phase and attainment of first mating using conventional and machine learning approaches.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA total of 510 female piglets from 77 litters sired by eight boars of the same genetic line were monitored from birth to approximately 220 days of age under commercial farm conditions. Recorded variables included birth weight, transition weight (40–46 days), body weight at ~220 days, and average daily gain (ADG) across growth intervals. Litter characteristics comprised total born, number born alive, number born dead, female proportion, and selection ratio. Variance components attributable to sire and dam were estimated using linear mixed-effects models. Progression to transition (n = 346/520) and attainment of first mating (n = 346 monitored) were analysed using logistic regression and Random Forest models with stratified 10-fold cross-validation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eBirth weight was positively correlated with transition weight (r = 0.51, p \u0026lt; 0.01) and early ADG (r = 0.34, p \u0026lt; 0.01), but showed weaker associations with body weight at 220 days (r = 0.17, p \u0026lt; 0.01). Litter size negatively affected birth weight (r = –0.29, p \u0026lt; 0.01) but was not associated with weight at 220 days. Maternal effects accounted for 39.9% of birth weight variance, declining to 10.5% at 220 days, whereas paternal variance remained below 3% across traits (h² = 0.006–0.13). Logistic regression identified birth weight as the strongest predictor of transition (OR = 1.66 per additional kg). Random Forest models demonstrated moderate discriminative ability for transition (AUC = 0.77) and first mating (AUC = 0.74), with early ADG emerging as the most influential predictor of first mating attainment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eEarly-life growth performance, particularly birth weight and pre-transition ADG, significantly influences gilt developmental progression under commercial conditions. Maternal and litter-level effects explain a substantial proportion of early growth variability. The integration of machine learning approaches improves individual-level prediction beyond traditional regression models and supports data-driven gilt selection strategies aimed at enhancing reproductive efficiency and herd sustainability.\u003c/p\u003e","manuscriptTitle":"Early-life growth performance and litter characteristics predict gilt selection and first mating success under commercial conditions","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-24 04:41:35","doi":"10.21203/rs.3.rs-9148333/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-27T18:28:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"323955339211667278632702000440961611380","date":"2026-03-19T15:33:23+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-19T14:36:31+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-19T13:12:42+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-19T13:12:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Porcine Health Management","date":"2026-03-17T11:22:58+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"porcine-health-management","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"phmj","sideBox":"Learn more about [Porcine Health Management](http://porcinehealthmanagement.biomedcentral.com/)","snPcode":"40813","submissionUrl":"https://submission.nature.com/new-submission/40813/3","title":"Porcine Health Management","twitterHandle":"@animalplantsci","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"638cb2aa-e3ca-429c-9e84-ded73d843e7f","owner":[],"postedDate":"March 24th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-24T04:41:35+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-24 04:41:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9148333","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9148333","identity":"rs-9148333","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}