NL-FuRBe: Precision Diagnosis of Citrus Leaf Diseases using Image Enhancement and Non-Linear Fuzzy Ranking Ensemble Approach

NL-FuRBe: Precision Diagnosis of Citrus Leaf Diseases using Image Enhancement and Non-Linear Fuzzy Ranking Ensemble 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 NL-FuRBe: Precision Diagnosis of Citrus Leaf Diseases using Image Enhancement and Non-Linear Fuzzy Ranking Ensemble Approach Bobbinpreet Kaur, Shashi Kant Gupta, Midhunchakkaravarthy Janarthan, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6898815/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Sep, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Citrus fruits, especially lemons, play a vital economic and nutritional role worldwide but are increasingly threatened by a wide range of diseases that diminish yield quality and quantity. Traditional manual and automated methods for disease detection requires domain expert, ample observation time, and is often ineffective during early infection stages. This paper presents a novel automated approach for the symptom based detection and classification of citrus leaf diseases using a Non-Linear Fuzzy Rank-Based Ensemble (NL-FuRBE) methodology, enhanced by image quality improvement techniques. The study emphasizes the significance of timely disease diagnosis in citrus crops, which are vital for global food security and economic stability. The methodology begins with image quality enhancement through Vector-Valued Anisotropic Diffusion (VAD) and morphological f iltering, evaluated using PSNR, SSIM, and NIQE metrics to ensure optimal visual clarity for classifier input. The core ensemble integrates three deep learning architectures—VGG19, AlexNet, and Xception—using a fuzzy rank-based scoring mechanism built on non-linear transformations (exponential, tanh, and sigmoid functions) to address prediction uncertainty and model bias. A comprehensive dataset of lemon leaf diseases, consisting of 1354 images across nine classes, was utilized for training and evaluation. Experimental results using five-fold cross-validation demonstrate that the proposed model achieves superior performance with an avearge accuracy of 96.51%, outperforming conventional ensemble and state-of-the-art approaches. The results validate the proposed NL-FuRBE as an effective, automated, and cost-efficient tool for precision agriculture and early disease diagnosis in citrus farming. Physical sciences/Engineering/Electrical and electronic engineering Biological sciences/Plant sciences/Plant physiology Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 02 Sep, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 04 Aug, 2025 Reviews received at journal 25 Jul, 2025 Reviewers agreed at journal 21 Jul, 2025 Reviews received at journal 07 Jul, 2025 Reviewers agreed at journal 01 Jul, 2025 Reviewers invited by journal 01 Jul, 2025 Editor assigned by journal 01 Jul, 2025 Editor invited by journal 17 Jun, 2025 Submission checks completed at journal 16 Jun, 2025 First submitted to journal 15 Jun, 2025 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. 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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-6898815","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":479119951,"identity":"d27f0c51-9584-4e52-a4a0-c5fd850196b1","order_by":0,"name":"Bobbinpreet Kaur","email":"","orcid":"","institution":"Lincoln University College","correspondingAuthor":false,"prefix":"","firstName":"Bobbinpreet","middleName":"","lastName":"Kaur","suffix":""},{"id":479119952,"identity":"72c1b49c-9bac-4d34-9344-48ad67db05bf","order_by":1,"name":"Shashi Kant Gupta","email":"","orcid":"","institution":"Lincoln University College","correspondingAuthor":false,"prefix":"","firstName":"Shashi","middleName":"Kant","lastName":"Gupta","suffix":""},{"id":479119954,"identity":"3cb43667-752f-47ca-a9d9-c1cd1d2a6af6","order_by":2,"name":"Midhunchakkaravarthy Janarthan","email":"","orcid":"","institution":"Lincoln University College","correspondingAuthor":false,"prefix":"","firstName":"Midhunchakkaravarthy","middleName":"","lastName":"Janarthan","suffix":""},{"id":479119955,"identity":"2c147cc1-6d96-49db-8e18-1b5a94ffe3cf","order_by":3,"name":"Deema Mohammed Alsekait","email":"","orcid":"","institution":"Princess Nourah bint Abdulrahman University","correspondingAuthor":false,"prefix":"","firstName":"Deema","middleName":"Mohammed","lastName":"Alsekait","suffix":""},{"id":479119956,"identity":"17431db1-8351-42fd-9f7d-6ec657a65b77","order_by":4,"name":"Diaa Salama AbdElminaam","email":"data:image/png;base64,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","orcid":"","institution":"Benha University","correspondingAuthor":true,"prefix":"","firstName":"Diaa","middleName":"Salama","lastName":"AbdElminaam","suffix":""}],"badges":[],"createdAt":"2025-06-15 14:23:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6898815/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6898815/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-16923-4","type":"published","date":"2025-09-02T15:57:07+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":90827910,"identity":"2bf2b3d3-c40f-42b9-bd03-1c68bd4fe10c","added_by":"auto","created_at":"2025-09-08 16:02:45","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1668393,"visible":true,"origin":"","legend":"","description":"","filename":"NLFurbeScientificreportsedited.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6898815/v1_covered_357ec276-d330-445f-b3fb-012478988601.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"NL-FuRBe: Precision Diagnosis of Citrus Leaf Diseases using Image Enhancement and Non-Linear Fuzzy Ranking Ensemble Approach","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6898815/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6898815/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Citrus fruits, especially lemons, play a vital economic and nutritional role worldwide but are increasingly threatened by a wide range of diseases that diminish yield quality and quantity. Traditional manual and automated methods for disease detection requires domain expert, ample observation time, and is often ineffective during early infection stages. This paper presents a novel automated approach for the symptom based detection and classification of citrus leaf diseases using a Non-Linear Fuzzy Rank-Based Ensemble (NL-FuRBE) methodology, enhanced by image quality improvement techniques. The study emphasizes the significance of timely disease diagnosis in citrus crops, which are vital for global food security and economic stability. The methodology begins with image quality enhancement through Vector-Valued Anisotropic Diffusion (VAD) and morphological f iltering, evaluated using PSNR, SSIM, and NIQE metrics to ensure optimal visual clarity for classifier input. 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