A Systematic Review, Bibliometric Analysis, and Meta-Analysis of Breed Adaptation and Sustainable Systems for Enhanced Beef Cattle Performance in Mozambique

A Systematic Review, Bibliometric Analysis, and Meta-Analysis of Breed Adaptation and Sustainable Systems for Enhanced Beef Cattle Performance in Mozambique | 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 A Systematic Review, Bibliometric Analysis, and Meta-Analysis of Breed Adaptation and Sustainable Systems for Enhanced Beef Cattle Performance in Mozambique Virgilio Juma Ali, Arsenio Mario Caetano, Sergio Abilio Azevedo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9105932/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Beef cattle production in Mozambique faces productivity constraints due to heat stress, limited adoption of sustainable practices, and use of non-adapted breeds. This study integrated systematic review (n = 57 publications), bibliometric analysis, and mixed-effects meta-analysis (n = 15 studies, 578 animals) to quantify the effects of breed adaptation and production system sustainability on daily weight gain in Mozambican cattle. Adapted breeds (Landim, Nguni, Angoni) showed significantly higher weight gain (+ 0.278 kg/day, p < 0.05) compared to non-adapted breeds, while sustainable management practices (shading, rotational grazing, improved feeding) added + 0.194 kg/day. The final predictive model explained 98.3% of observed variability (R²=0.983) with low prediction error (RMSE = 0.124 kg/day). Adapted breeds under sustainable systems achieved the highest predicted weight gain (0.78 kg/day), approaching commercial viability (0.8 kg/day), whereas non-adapted breeds under traditional systems showed the lowest performance (0.31 kg/day). Geographic distribution revealed research concentration in southern/central regions (82.5% of studies) and underrepresentation of northern Mozambique. These findings demonstrate synergistic benefits of aligning genetic adaptation with sustainable management, supporting evidence-based policies for resilient beef production in Mozambique and similar tropical systems. Indigenous cattle Landim Nguni Climate resilience Smallholder systems Sub-Saharan Africa Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 21 Apr, 2026 Reviews received at journal 17 Apr, 2026 Reviews received at journal 09 Apr, 2026 Reviews received at journal 07 Apr, 2026 Reviewers agreed at journal 06 Apr, 2026 Reviewers agreed at journal 01 Apr, 2026 Reviewers agreed at journal 31 Mar, 2026 Reviewers invited by journal 31 Mar, 2026 Editor assigned by journal 26 Mar, 2026 Submission checks completed at journal 24 Mar, 2026 First submitted to journal 24 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. 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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-9105932","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":615809375,"identity":"a4b0bb51-91cc-4a40-b96e-57a14ffa70da","order_by":0,"name":"Virgilio Juma Ali","email":"data:image/png;base64,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","orcid":"","institution":"Federal University of Lavras","correspondingAuthor":true,"prefix":"","firstName":"Virgilio","middleName":"Juma","lastName":"Ali","suffix":""},{"id":615809377,"identity":"32282eba-7acc-4a83-a0ce-822e15831cef","order_by":1,"name":"Arsenio Mario Caetano","email":"","orcid":"","institution":"Federal University of Lavras","correspondingAuthor":false,"prefix":"","firstName":"Arsenio","middleName":"Mario","lastName":"Caetano","suffix":""},{"id":615809378,"identity":"5e49a0af-ab67-46ca-9723-530c79516a52","order_by":2,"name":"Sergio Abilio Azevedo","email":"","orcid":"","institution":"Federal University of Lavras","correspondingAuthor":false,"prefix":"","firstName":"Sergio","middleName":"Abilio","lastName":"Azevedo","suffix":""}],"badges":[],"createdAt":"2026-03-12 14:25:42","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9105932/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9105932/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106094977,"identity":"664c4ea1-eb91-4223-8467-113583e4fb87","added_by":"auto","created_at":"2026-04-03 11:43:51","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":475176,"visible":true,"origin":"","legend":"","description":"","filename":"BreedAdaptationandSustainableSystemsEnhanceBeefCattlePerformanceinMozambiqueASystematicReviewBibliometricAnalysisandMetaAnalysis.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9105932/v1_covered_dc17338d-d2be-4844-92ab-b425a15f8c80.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Systematic Review, Bibliometric Analysis, and Meta-Analysis of Breed Adaptation and Sustainable Systems for Enhanced Beef Cattle Performance in Mozambique","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":"discover-animals","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Animals](https://link.springer.com/journal/44338)","snPcode":"44338","submissionUrl":"https://submission.springernature.com/new-submission/44338/3","title":"Discover Animals","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Indigenous cattle, Landim, Nguni, Climate resilience, Smallholder systems, Sub-Saharan Africa","lastPublishedDoi":"10.21203/rs.3.rs-9105932/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9105932/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBeef cattle production in Mozambique faces productivity constraints due to heat stress, limited adoption of sustainable practices, and use of non-adapted breeds. This study integrated systematic review (n\u0026thinsp;=\u0026thinsp;57 publications), bibliometric analysis, and mixed-effects meta-analysis (n\u0026thinsp;=\u0026thinsp;15 studies, 578 animals) to quantify the effects of breed adaptation and production system sustainability on daily weight gain in Mozambican cattle. Adapted breeds (Landim, Nguni, Angoni) showed significantly higher weight gain (+\u0026thinsp;0.278 kg/day, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) compared to non-adapted breeds, while sustainable management practices (shading, rotational grazing, improved feeding) added\u0026thinsp;+\u0026thinsp;0.194 kg/day. The final predictive model explained 98.3% of observed variability (R\u0026sup2;=0.983) with low prediction error (RMSE\u0026thinsp;=\u0026thinsp;0.124 kg/day). 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