Genetic Diversity among Yam (Dioscorea cayenensis Lam. Complex) Landraces using Morphological Traits | 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 Article Genetic Diversity among Yam (Dioscorea cayenensis Lam. Complex) Landraces using Morphological Traits Wendawek A. Mengesha, Shambel W. Waketa, Zelalem G. Tolesa This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9254666/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Yams ( Dioscorea cayenensis Lam. complex ) are the fourth most economically important tuber crop next to Irish potatoes, cassava, and sweet potatoes. The study was conducted to estimate the magnitude of genetic variation, association between tuber yield and related traits and to identify the most influential character(s) involving twenty landraces collections of yam for effective selection and conservation. The experiment was conducted at Hawassa University's main campus research farm using a randomized complete block design in three replications. Data were collected for growth and yield parameters. Mean values were used to determine characters' phenotypic and genotypic variances, phenotypic, genotypic and environmental coefficients of variation. Broad sense heritability and genetic advance percentage of mean were estimated for each trait. Analysis variance of characters revealed significant differences (p < 0.01) among the landraces. Estimate of phenotypic and genotypic coefficients of variation showed variability among the farmers’ varieties. The difference between phenotypic and genotypic coefficients of variation was low for traits studied, which indicates the lower environmental influences on these traits. The highest genotypic and phenotypic coefficients of variations and the maximum heritability were recorded for leaf lobe length. A significant positive phenotypic correlation was recorded between tuber fresh weight and seven characters. Selection of farmers’ varieties based on high genotypic coefficient variation coupled with high heritability and genetic advance as percent mean value are useful tools in yam improvement programs. In this regard, leaf lobe length, number of stems, tuber fresh weight and tuber dry weight should be given due importance in yam breeding programs. Biological sciences/Genetics Biological sciences/Plant sciences Correlation Genetic Variation Heritability Yam Full Text Additional Declarations No competing interests reported. Supplementary Files SM1.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 21 Apr, 2026 Reviewers agreed at journal 12 Apr, 2026 Reviewers agreed at journal 08 Apr, 2026 Reviewers invited by journal 08 Apr, 2026 Editor assigned by journal 08 Apr, 2026 Editor invited by journal 07 Apr, 2026 Submission checks completed at journal 03 Apr, 2026 First submitted to journal 03 Apr, 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-9254666","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":621739749,"identity":"8489dae2-fda6-4a46-8705-ea3c735b6017","order_by":0,"name":"Wendawek A. 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