Modeling the impact of improved seed varieties on common bean productivity in agroecological zones of Tanzania: A stochastic simulation approach

Modeling the impact of improved seed varieties on common bean productivity in agroecological zones of Tanzania: A stochastic simulation approach | 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 Modeling the impact of improved seed varieties on common bean productivity in agroecological zones of Tanzania: A stochastic simulation approach Ibrahim L. Kadigi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9311720/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 Common beans are a vital source of nutrition and income for smallholder farmers in Tanzania, yet productivity remains low due to continued reliance on traditional seed varieties. This study evaluates the impact of improved seed varieties on bean yield across Tanzania’s agroecological zones (AEZs), using a non-parametric Monte Carlo simulation based on nationally representative data from the 2019/20 National Sample Census of Agriculture (NSCA). We compare yield distributions for farms using local versus improved seeds, simulating probabilities of achieving productivity thresholds of 0.6 t/ha (subsistence level) and 1.5 t/ha (global standard) across both long and short rainy seasons. Results show that improved seeds substantially increase the likelihood of attaining high yields, particularly during the short rainy season (SRS). In zones like the Lake and Eastern regions, improved seed users had a 42–49% chance of surpassing 1.5 t/ha, compared to just 34% for local seed users. However, these gains are accompanied by increased yield variability and risk, especially under less favorable seasonal conditions. During the long rainy season (LRS), both seed types were associated with a high probability (> 50%) of yields falling below 0.6 t/ha, highlighting seasonal sensitivity. The study underscores the importance of spatially targeted seed interventions and supports policies promoting access to improved seeds, extension services, and climate-resilient practices. These findings contribute to evidence-based strategies for enhancing food security and agricultural resilience in alignment with Sustainable Development Goal 2 (Zero Hunger). Biological sciences/Ecology Earth and environmental sciences/Ecology Earth and environmental sciences/Environmental sciences Biological sciences/Plant sciences stochastic simulation local seeds improved seeds bean productivity agroecological zones Tanzanian Full Text Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterial.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 06 May, 2026 Reviewers agreed at journal 21 Apr, 2026 Reviewers agreed at journal 20 Apr, 2026 Reviewers invited by journal 19 Apr, 2026 Editor invited by journal 08 Apr, 2026 Editor assigned by journal 03 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-9311720","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":626879429,"identity":"03382eae-8b53-4f66-8d66-2a772df90388","order_by":0,"name":"Ibrahim L. 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This study evaluates the impact of improved seed varieties on bean yield across Tanzania\u0026rsquo;s agroecological zones (AEZs), using a non-parametric Monte Carlo simulation based on nationally representative data from the 2019/20 National Sample Census of Agriculture (NSCA). We compare yield distributions for farms using local versus improved seeds, simulating probabilities of achieving productivity thresholds of 0.6 t/ha (subsistence level) and 1.5 t/ha (global standard) across both long and short rainy seasons. Results show that improved seeds substantially increase the likelihood of attaining high yields, particularly during the short rainy season (SRS). In zones like the Lake and Eastern regions, improved seed users had a 42\u0026ndash;49% chance of surpassing 1.5 t/ha, compared to just 34% for local seed users. However, these gains are accompanied by increased yield variability and risk, especially under less favorable seasonal conditions. During the long rainy season (LRS), both seed types were associated with a high probability (\u0026gt;\u0026thinsp;50%) of yields falling below 0.6 t/ha, highlighting seasonal sensitivity. The study underscores the importance of spatially targeted seed interventions and supports policies promoting access to improved seeds, extension services, and climate-resilient practices. 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