Automatic estimation of severity level for late blight in images of celery leaves through the firefly algorithm

Automatic estimation of severity level for late blight in images of celery leaves through the firefly algorithm | 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 Automatic estimation of severity level for late blight in images of celery leaves through the firefly algorithm Niriaska Perozo, Wilfredo Angulo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7768279/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 Celery (Apium graveolens L. var. Dulce) is a vegetable valued for its flavor and nutritional properties, used both in culinary applications and traditional medicine for its health benefits. Its growing global demand has led to an increase in its cultivation, which is threatened by diseases such as late blight in leaves and stems. The detection and quantification of the severity of this disease are crucial to mitigate crop losses; however, visual observation is imprecise over large cultivation areas. In this work, we present an innovative method for the segmentation and classification of images of celery leaves affected by late blight, aiming to automate the estimation of severity levels. Using thresholded and adaptive segmentation based on the Firefly Algorithm, healthy and diseased areas in the images are delineated. The threshold is optimized through objective functions based on Tsallis, Kapur, and Otsu functions, resulting in an accuracy of 98.8% with Tsallis entropy. Additionally, a scale is proposed to clearly identify color variations associated with late blight, facilitating an accurate estimation of disease severity level. Artificial Intelligence and Machine Learning Late blight detection Celery leaf segmentation Firefly Algorithm optimization Disease severity estimation. 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. 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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-7768279","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":523916563,"identity":"fd485821-8f31-4052-9310-b964f66a3951","order_by":0,"name":"Niriaska Perozo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIiWNgGAWjYDACZgaGAwwMCXC+HIQqIEGLMYQyIGgXQktiAyEt5uy8Dw/8+JMmzyDdfOzDhz826RuOnz3A8AOPFstmdoODvW05hg0yx5JnzuBJy91wJi+BsQePFoPDbAwHeBsqGBskcoyZeSQO5264wWPAjM9hIC0H//ypsG+QyP/MzGNwON2AGC2HedhyEoG2MDPzJBxOIE6LbFtacpvMMWPGGQfSDGeeyTE4iNcv548xf3zzJ9m2X7r5MQMwxOT5jp8xfPCjArcWOGCTQOIcIEIDEEgQVjIKRsEoGAUjFAAA4o5McNeQCkcAAAAASUVORK5CYII=","orcid":"","institution":"Escuela de Ciencias Empresariales, Universidad Católica del Norte, Coquimbo, Chile","correspondingAuthor":true,"prefix":"","firstName":"Niriaska","middleName":"","lastName":"Perozo","suffix":""},{"id":523916564,"identity":"071a2b81-8e3d-4861-8c2f-96627d5511cc","order_by":1,"name":"Wilfredo Angulo","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0003-1908-9554","institution":"PUCE and YACHAY","correspondingAuthor":true,"prefix":"","firstName":"Wilfredo","middleName":"","lastName":"Angulo","suffix":""}],"badges":[],"createdAt":"2025-10-02 17:27:32","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-7768279/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7768279/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":92708106,"identity":"ed1bdef5-c277-40a1-9046-fb0fea46a663","added_by":"auto","created_at":"2025-10-03 10:21:28","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":706126,"visible":true,"origin":"","legend":"","description":"","filename":"perozoetal20225.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7768279/v1_covered_186796cc-8afe-4210-81e2-d10849d489ae.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eAutomatic estimation of severity level for late blight in images of celery leaves through the firefly algorithm\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Auburn University at Montgomery","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":"Late blight detection, Celery leaf segmentation, Firefly Algorithm optimization, Disease severity estimation.","lastPublishedDoi":"10.21203/rs.3.rs-7768279/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7768279/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCelery (Apium graveolens L. var. 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