LeafGenEx-A Novel Method for Generating Healthy and Diseased Wheat Leaf Images using CycleGAN

LeafGenEx-A Novel Method for Generating Healthy and Diseased Wheat Leaf Images using CycleGAN | 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 LeafGenEx-A Novel Method for Generating Healthy and Diseased Wheat Leaf Images using CycleGAN Jigna Patel, Aditya Pachchigar, Jitali Patel This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4467039/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 LeafGenEx, an innovative approach to wheat leaf disease detection, uses data augmentation, deep learning, and explainable AI to improve disease detection accuracy. The procedure starts with preprocessing methods, such as image flipping, rotation, and cropping, to extend the original dataset. Segmentation is eventually carried out utilising a pre-trained ResNet network and GradCAM, allowing for exact identification of disease-affected regions. An upgraded CycleGAN model is used to produce synthetic images of healthy and diseased leaves, yielding a higher Fréchet Inception Distance (FID) score than previous DCGAN and CycleGAN models. The generated images are combined with the original dataset to form a comprehensive dataset for training a deep learning detection model. To categorise leaf images according to their different diseases, the authors use a method based on transfer learning with InceptionV3. GradCAM, an explainable AI approach, is used to evaluate the deep learning model's results and determine the most important leaf sections for disease detection. LeafGenEx's effectiveness is proved by its capacity to generate high-quality synthetic images, improve disease detection accuracy, and produce interpretable data, making it an important tool for precision agriculture and early disease intervention. Biological sciences/Biotechnology/Plant biotechnology/Agricultural genetics Biological sciences/Computational biology and bioinformatics/Computational models Biological sciences/Computational biology and bioinformatics/Data integration Biological sciences/Computational biology and bioinformatics/Data processing Biological sciences/Computational biology and bioinformatics/Image processing Biological sciences/Plant sciences/Plant biotechnology Biological sciences/Plant sciences/Plant immunity LeafGenEx GradCAM CycleGAN FID DCGAN InceptionV3 Full Text Additional Declarations No competing interests reported. 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-4467039","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":312683189,"identity":"6908d324-f78a-4e9f-ac54-8c646f210640","order_by":0,"name":"Jigna Patel","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEUlEQVRIiWNgGAWjYBACxmYk9oEPDBIQZgKIYCakhY2B4eAMYrQgAFDLYR5iHMbczn7twY8/DHn885sPHLbdYZGv237G7MEDBjt5BnbeA9gdxlNu2NvGUCxxjC3hcO4ZCcttZ3LMDRIYkg0bmPkScGhJk+BtYEhsOMZjcDi3TcLA7ECOmUQCAzMQ8Rjg0iL55w9D4vxj/B8OW4K0nH8D0lKPRwv7MWkeNobEDcd4GA4zgrTcANtyGJ8tbNKybRLFhsfSDA72grU8K5NIMDhu2IZDi2H/8WeSb/7Y5MkdPvzwwc+2OqDDkrdJ/qiolufnP4NdSwPYKAn0sDEARxRWAAz9ByAaXcsoGAWjYBSMAgQAAMBcV2ggwfivAAAAAElFTkSuQmCC","orcid":"","institution":"Nirma University","correspondingAuthor":true,"prefix":"","firstName":"Jigna","middleName":"","lastName":"Patel","suffix":""},{"id":312683190,"identity":"27e57a58-1ddc-4a54-b4b6-26f809e02912","order_by":1,"name":"Aditya Pachchigar","email":"","orcid":"","institution":"Nirma University","correspondingAuthor":false,"prefix":"","firstName":"Aditya","middleName":"","lastName":"Pachchigar","suffix":""},{"id":312683191,"identity":"979b8149-0b2f-42c7-86c0-821838aadeb3","order_by":2,"name":"Jitali Patel","email":"","orcid":"","institution":"Nirma University","correspondingAuthor":false,"prefix":"","firstName":"Jitali","middleName":"","lastName":"Patel","suffix":""}],"badges":[],"createdAt":"2024-05-23 12:59:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4467039/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4467039/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":64917478,"identity":"8d1e947c-1ffc-4493-b92d-72aebf633886","added_by":"auto","created_at":"2024-09-20 11:05:40","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1128158,"visible":true,"origin":"","legend":"","description":"","filename":"LeafGenEx.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4467039/v1_covered_5a8ce02f-c3a2-4f18-bc6e-45520d272d12.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"LeafGenEx-A Novel Method for Generating Healthy and Diseased Wheat Leaf Images using CycleGAN","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"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":"LeafGenEx, GradCAM, CycleGAN, FID, DCGAN, InceptionV3","lastPublishedDoi":"10.21203/rs.3.rs-4467039/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4467039/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"LeafGenEx, an innovative approach to wheat leaf disease detection, uses data augmentation, deep learning, and explainable AI to improve disease detection accuracy. 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