Development of a Simulated Annealing–Adaptive Neuro-Fuzzy Inference System (SA-ANFIS) Model for Sorghum Seed Intra-Row Spacing Optimization

Development of a Simulated Annealing–Adaptive Neuro-Fuzzy Inference System (SA-ANFIS) Model for Sorghum Seed Intra-Row Spacing Optimization | 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 Development of a Simulated Annealing–Adaptive Neuro-Fuzzy Inference System (SA-ANFIS) Model for Sorghum Seed Intra-Row Spacing Optimization Ibrahim Abubakar, ABDULLAHI Ibrahim Mohammed, BALAMI Audu Ayuba, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9586195/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Uneven intra-row seed placement remains a major challenge in precision sorghum planting, reducing stand uniformity and input-use efficiency. This study developed and evaluated a Simulated Annealing–optimized Adaptive Neuro-Fuzzy Inference System (SA-ANFIS) for predicting sorghum seed spacing under varying soil-moisture levels and planter forward speeds. Experimental data from an instrumented smart planter were screened, filtered, normalized, and partitioned using fixed procedures to improve transparency and minimize bias. The final dataset comprised 120 valid observations, using soil moisture and planter speed as inputs and intra-row spacing as the output. A first-order Sugeno ANFIS was first trained using hybrid learning, and its premise parameters were subsequently optimized using Simulated Annealing. Model performance was assessed using MSE, RMSE, R², Bland–Altman analysis, and response-surface evaluation. Optimization reduced normalized training MSE from 0.0028 to 0.0011. Test performance improved from RMSE = 0.8171 cm and R² = 0.830 for the baseline model to RMSE = 0.4595 cm and R² = 0.898 for the optimized model, representing a 43.8% reduction in prediction error. The optimized controller was successfully implemented on an Arduino Mega 2560 with a 50–100 ms control interval, demonstrating practical embedded feasibility. Although validation was limited to prototype testing, the SA-ANFIS framework provides a reliable and reproducible basis for intelligent sorghum seed-spacing control. Sorghum planting intra-row seed spacing ANFIS simulated annealing precision agriculture seed metering control embedded implementation Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 15 May, 2026 Reviews received at journal 12 May, 2026 Reviewers agreed at journal 09 May, 2026 Reviewers invited by journal 07 May, 2026 Editor assigned by journal 06 May, 2026 Submission checks completed at journal 06 May, 2026 First submitted to journal 01 May, 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-9586195","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":640995325,"identity":"c1bf486f-5da2-4e9e-9d00-7c67e708401a","order_by":0,"name":"Ibrahim Abubakar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEUlEQVRIie3QsUoDMRzH8d8RSJdcXU9SvFfIUbCIij6K4aBbS+Ggi8tBIZPdCyp9hXNR3O4Q6tT6AFnqrqA49gaTgpOE3iiS73IQ7kP+/wA+3x+MRgCBAARhwRo4gGDmmDUkxHy6uwm2xCTALG9A2nz6+jUa3ce9Vri4DJUY9lgZrN8VhvG5Y7DOc5fPhE4eJ+2+NiQ7muYkuVXIktK1Sx+cCR0UT+xQD1QtixdQHirIu9xJyMaQM0uygRKWtDY7CLW3SEvIlixzSiyZO9annQU9NiQ1u6S8XpldrqrJ/s0qkoWDxNeKaFbr04e9ZfU5G9sXS6uPt/GJnDsG+9UFENh/I4iyOfkZoOktPp/P99/7BjUdVYTKjBxfAAAAAElFTkSuQmCC","orcid":"","institution":"Waziri Umaru Federal Polytechnic","correspondingAuthor":true,"prefix":"","firstName":"Ibrahim","middleName":"","lastName":"Abubakar","suffix":""},{"id":640995326,"identity":"d1de141e-ba0c-4b87-9d65-efd7ff58a670","order_by":1,"name":"ABDULLAHI Ibrahim Mohammed","email":"","orcid":"","institution":"Federal University of Technology","correspondingAuthor":false,"prefix":"","firstName":"ABDULLAHI","middleName":"Ibrahim","lastName":"Mohammed","suffix":""},{"id":640995327,"identity":"4421ccc2-c260-4e9a-80a0-fc1a545559d9","order_by":2,"name":"BALAMI Audu Ayuba","email":"","orcid":"","institution":"Federal University of Technology","correspondingAuthor":false,"prefix":"","firstName":"BALAMI","middleName":"Audu","lastName":"Ayuba","suffix":""},{"id":640995328,"identity":"3d6c5fe3-024e-478d-ba09-b086e7a3f804","order_by":3,"name":"IDAH Peter Abah","email":"","orcid":"","institution":"Federal University of Technology","correspondingAuthor":false,"prefix":"","firstName":"IDAH","middleName":"Peter","lastName":"Abah","suffix":""}],"badges":[],"createdAt":"2026-05-01 12:54:45","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9586195/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9586195/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109436515,"identity":"37d84afc-44b8-4e92-b08e-5f6757040cd3","added_by":"auto","created_at":"2026-05-18 06:22:39","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":535597,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscriptspacing2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9586195/v1_covered_f37e23eb-ef12-4a54-9b1f-dbf34cb74d27.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Development of a Simulated Annealing–Adaptive Neuro-Fuzzy Inference System (SA-ANFIS) Model for Sorghum Seed Intra-Row Spacing Optimization","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":"scientific-journal-of-king-faisal-university-basic-and-applied-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Scientific Journal of King Faisal University: Basic and Applied Sciences](https://link.springer.com/journal/44523)","snPcode":"44523","submissionUrl":"https://submission.springernature.com/new-submission/44523/3","title":"Scientific Journal of King Faisal University: Basic and Applied Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Sorghum planting, intra-row seed spacing, ANFIS, simulated annealing, precision agriculture, seed metering control, embedded implementation","lastPublishedDoi":"10.21203/rs.3.rs-9586195/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9586195/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eUneven intra-row seed placement remains a major challenge in precision sorghum planting, reducing stand uniformity and input-use efficiency. This study developed and evaluated a Simulated Annealing\u0026ndash;optimized Adaptive Neuro-Fuzzy Inference System (SA-ANFIS) for predicting sorghum seed spacing under varying soil-moisture levels and planter forward speeds. Experimental data from an instrumented smart planter were screened, filtered, normalized, and partitioned using fixed procedures to improve transparency and minimize bias. The final dataset comprised 120 valid observations, using soil moisture and planter speed as inputs and intra-row spacing as the output. A first-order Sugeno ANFIS was first trained using hybrid learning, and its premise parameters were subsequently optimized using Simulated Annealing. Model performance was assessed using MSE, RMSE, R\u0026sup2;, Bland\u0026ndash;Altman analysis, and response-surface evaluation. Optimization reduced normalized training MSE from 0.0028 to 0.0011. Test performance improved from RMSE\u0026thinsp;=\u0026thinsp;0.8171 cm and R\u0026sup2; = 0.830 for the baseline model to RMSE\u0026thinsp;=\u0026thinsp;0.4595 cm and R\u0026sup2; = 0.898 for the optimized model, representing a 43.8% reduction in prediction error. The optimized controller was successfully implemented on an Arduino Mega 2560 with a 50\u0026ndash;100 ms control interval, demonstrating practical embedded feasibility. Although validation was limited to prototype testing, the SA-ANFIS framework provides a reliable and reproducible basis for intelligent sorghum seed-spacing control.\u003c/p\u003e","manuscriptTitle":"Development of a Simulated Annealing–Adaptive Neuro-Fuzzy Inference System (SA-ANFIS) Model for Sorghum Seed Intra-Row Spacing Optimization","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-18 06:22:28","doi":"10.21203/rs.3.rs-9586195/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"191833830604005756765823669638051926559","date":"2026-05-15T17:43:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-12T04:01:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"94079262743889073374774460182520654813","date":"2026-05-09T13:47:26+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-05-07T08:38:54+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-06T07:17:39+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-05-06T07:17:17+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Journal of King Faisal University: Basic and Applied Sciences","date":"2026-05-01T12:43:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-journal-of-king-faisal-university-basic-and-applied-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Scientific Journal of King Faisal University: Basic and Applied Sciences](https://link.springer.com/journal/44523)","snPcode":"44523","submissionUrl":"https://submission.springernature.com/new-submission/44523/3","title":"Scientific Journal of King Faisal University: Basic and Applied Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fd8d1b2f-8a73-4a2b-b650-cbfe61dbfb5c","owner":[],"postedDate":"May 18th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"191833830604005756765823669638051926559","date":"2026-05-15T17:43:41+00:00","index":18,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-12T04:01:04+00:00","index":15,"fulltext":""},{"type":"reviewerAgreed","content":"94079262743889073374774460182520654813","date":"2026-05-09T13:47:26+00:00","index":14,"fulltext":""},{"type":"reviewersInvited","content":"6","date":"2026-05-07T08:38:54+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-06T07:17:39+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-05-06T07:17:17+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-18T06:22:28+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-18 06:22:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9586195","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9586195","identity":"rs-9586195","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}