Ml-powered Smartagro Guidance Platform for Accurate Farming

Ml-powered Smartagro Guidance Platform for Accurate Farming | 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Article Ml-powered Smartagro Guidance Platform for Accurate Farming Rajasathiya, Palanikumar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7026560/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Smart farming technologies can considerably improve agricultural production, a key driver of the international economy. Smart Agro-Advisory Framework provides individualized advice regarding appropriate crops and fertilizers on the basis of environmental factors and soil properties with the help of Deep Learning and Machine Learning. It also executes early plant disease detection via image analysis. In contrast to traditional methods that depend on single factors, this system considers several soil and climatic parameters to give precise advice. One of the distinguishing features is the inclusion of a Leaf Color Chart (LCC), which allows for early detection of nutrient deficiencies and plant diseases. Machine Learning algorithms like Random Forest, LSTM, CNN, and Reinforcement Learning are used to process and analyze a dataset of agricultural instances with enhanced accuracy. The AI-based solution helps in sustainable agriculture by optimizing resource utilization and minimizing excessive use of fertilizers and pesticides. Artificial Intelligence and Machine Learning Artificial Intelligence Crop Prediction Soil Health Analysis Sustainable Agriculture Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted 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-7026560","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":479457642,"identity":"2ed9c6cb-67fc-451d-a968-b273a262c694","order_by":0,"name":"Rajasathiya","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBElEQVRIiWNgGAWjYHCCBDDBxsDA+AAqYgBGBLQYgLQww9QR1AJWBNLHJoHQggeYtx94+PFHzZ88PonkZ9UFf+7lM7A3b5NgKLiDU4vMmYRkaZ5jBsVsEmlmt2e2FVs28Bwrk2AweIZTiwRDQoI0A5tBYptEgtlt3oYEAwaJHDOglsO4tfA/SP754x9IS/q3Yp4/QC3ybwhokUhIk+BtA2nJMWPmYQPZwkNIy4M0a94+48Q2njfF0jPbEgzYeNKKLRLwOiwn+eaPb3KJ89vTN34uADqMn/3wxhsf/uDWwsDAkwChBRIYmEE0G4hIwKOBgYH9AITmPwDRMgpGwSgYBaMAHQAAmhJNES0T1yYAAAAASUVORK5CYII=","orcid":"https://orcid.org/0009-0006-9237-3630","institution":"P.S.R.R College of Engineering","correspondingAuthor":true,"prefix":"","firstName":"","middleName":"","lastName":"Rajasathiya","suffix":""},{"id":479457643,"identity":"ea562657-176e-49ed-a375-0a9e4c098a3c","order_by":1,"name":"Palanikumar","email":"","orcid":"","institution":"P.S.R Engineering College","correspondingAuthor":false,"prefix":"","firstName":"","middleName":"","lastName":"Palanikumar","suffix":""}],"badges":[],"createdAt":"2025-07-02 07:42:10","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-7026560/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7026560/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86003462,"identity":"b8fcae3c-882d-4863-9859-9213bc7909d8","added_by":"auto","created_at":"2025-07-04 08:03:58","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":629020,"visible":true,"origin":"","legend":"","description":"","filename":"SMARTAGROADVISORYSYSTEM.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7026560/v1_covered_0312306f-0a66-4eb5-896f-378d75bcaa29.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eMl-powered Smartagro Guidance Platform for Accurate Farming\u003c/strong\u003e\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"P.S.R.R College of Engineering","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Artificial Intelligence, Crop Prediction, Soil Health Analysis, Sustainable Agriculture","lastPublishedDoi":"10.21203/rs.3.rs-7026560/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7026560/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSmart farming technologies can considerably improve agricultural production, a key driver of the international economy. 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