Epidemiological studies of early blight of potato Alternaria solani (Sorauer) and it’s occurrence and severity

Epidemiological studies of early blight of potato Alternaria solani (Sorauer) and it’s occurrence and severity | 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 Epidemiological studies of early blight of potato Alternaria solani (Sorauer) and it’s occurrence and severity Shivam ., S K Biswas, Saurabh Kumar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9611361/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Potato (Solanum tuberosum L.) is one of the world's most important food crops and it’s highly susceptible to early blight - a destructive foliar disease caused by the fungal pathogen Alternaria solani (Sorauer). Despite its widespread occurrence, relatively less known about how local weather patterns shape the spread and intensity of early blight epidemic across the different agro-climatic zones of Uttar Pradesh, which is India's leading potato-producing state. To investigate this gap, a systematic field survey was carried out during the Rabi season (October–December 2022) at five geographically distinct locations: Kanpur, Kannauj, Agra, Meerut and Varanasi. Disease severity was assessed at weekly intervals using a standard 0–5 rating scale and the percent disease index (PDI) was calculated by using the McKinney formula. Daily meteorological data covering maximum and minimum temperature, maximum and minimum relative humidity, sunshine duration, evaporation, rainfall and soil temperature at 5 cm and 30 cm depth were obtained from local weather stations and correlated with disease progression using Pearson's correlation coefficients and stepwise multiple linear regression. The earliest disease onset was recorded at Agra (9 November 2022, 0.68%) and the latest at Kanpur (22 November 2022, 0.24%). Peak severity was highest at Agra (38.46%) and lowest at Kanpur (27.68%). Across all locations, maximum and minimum temperatures showed consistent, strong negative correlations with disease severity, suggesting that declining temperatures as the Rabi season advances create progressively more conducive conditions for disease build-up. Relative humidity and rainfall show location-specific positive associations with epidemic development. Stepwise regression identified minimum temperature (Tmin) as the dominant predictor at Kanpur, sunshine and evaporation at Meerut and sunshine together with soil temperature at Varanasi. These findings underscore the importance of region-specific epidemiological models and provide a scientific foundation for weather-driven early warning systems for early blight management in Uttar Pradesh. Full Text Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 06 May, 2026 Reviewers invited by journal 06 May, 2026 Editor assigned by journal 05 May, 2026 First submitted to journal 04 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-9611361","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":635462011,"identity":"ebca57e9-ef92-40ab-9e0f-22f1d5b50739","order_by":0,"name":"Shivam .","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIiWNgGAWjYDACCcYGMM3P3nzwAZDm4SNai2TPsWQDkBY2wlqgtMEMHzMwm6AW+dnNbRI/c+zsNkiwpVV+zbGTYWNgfvjoBh4tBncOtkn2bktO3i7dfOy27LZkoMPYjI1z8GmRSGw24N3GnGw551jabcltzEAtPGzS+LTIz0hsNvy7rT7Z4EaOWbHktnrCWhhuJDY+5t122A6khfHjtsOEtRiAtMhuO54ACmRpxm3HediYCfhFfkb6g4Nvt1Xbg6Ly408I4+FjvA6DgsQGIMHMA2IyE6EcBOxBBOMPIlWPglEwCkbByAIAlh5Kv415T4cAAAAASUVORK5CYII=","orcid":"https://orcid.org/0009-0007-5856-190X","institution":"RLBCAU: Rani Lakshmi Bai Central Agricultural University","correspondingAuthor":true,"prefix":"","firstName":"Shivam","middleName":"","lastName":".","suffix":""},{"id":635462012,"identity":"cfd91eab-9b6a-4921-92e9-eb8bd9b86df7","order_by":1,"name":"S K Biswas","email":"","orcid":"","institution":"CSA University of Agriculture and Technology: Chandra Shekhar Azad University of Agriculture and Technology","correspondingAuthor":false,"prefix":"","firstName":"S","middleName":"K","lastName":"Biswas","suffix":""},{"id":635462013,"identity":"b806965f-74d8-415c-b88a-eaac80103914","order_by":2,"name":"Saurabh Kumar","email":"","orcid":"","institution":"CSA University of Agriculture and Technology: Chandra Shekhar Azad University of Agriculture and Technology","correspondingAuthor":false,"prefix":"","firstName":"Saurabh","middleName":"","lastName":"Kumar","suffix":""}],"badges":[],"createdAt":"2026-05-04 18:42:56","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9611361/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9611361/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109296453,"identity":"97bba51e-d398-471b-8265-30fbbef624ba","added_by":"auto","created_at":"2026-05-15 08:47:06","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":264215,"visible":true,"origin":"","legend":"","description":"","filename":"AlternariaSolani26.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9611361/v1_covered_1e326031-b049-4acc-a3dd-b3137731470e.pdf"}],"financialInterests":"","formattedTitle":"Epidemiological studies of early blight of potato Alternaria solani (Sorauer) and it’s occurrence and severity","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":"potato-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"potr","sideBox":"Learn more about [Potato Research](http://link.springer.com/journal/11540)","snPcode":"11540","submissionUrl":"https://www.editorialmanager.com/potr/default2.aspx","title":"Potato Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-9611361/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9611361/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Potato (Solanum tuberosum L.) is one of the world's most important food crops and it’s highly susceptible to early blight - a destructive foliar disease caused by the fungal pathogen Alternaria solani (Sorauer). Despite its widespread occurrence, relatively less known about how local weather patterns shape the spread and intensity of early blight epidemic across the different agro-climatic zones of Uttar Pradesh, which is India's leading potato-producing state. To investigate this gap, a systematic field survey was carried out during the Rabi season (October–December 2022) at five geographically distinct locations: Kanpur, Kannauj, Agra, Meerut and Varanasi. Disease severity was assessed at weekly intervals using a standard 0–5 rating scale and the percent disease index (PDI) was calculated by using the McKinney formula. Daily meteorological data covering maximum and minimum temperature, maximum and minimum relative humidity, sunshine duration, evaporation, rainfall and soil temperature at 5 cm and 30 cm depth were obtained from local weather stations and correlated with disease progression using Pearson's correlation coefficients and stepwise multiple linear regression. The earliest disease onset was recorded at Agra (9 November 2022, 0.68%) and the latest at Kanpur (22 November 2022, 0.24%). Peak severity was highest at Agra (38.46%) and lowest at Kanpur (27.68%). Across all locations, maximum and minimum temperatures showed consistent, strong negative correlations with disease severity, suggesting that declining temperatures as the Rabi season advances create progressively more conducive conditions for disease build-up. Relative humidity and rainfall show location-specific positive associations with epidemic development. Stepwise regression identified minimum temperature (Tmin) as the dominant predictor at Kanpur, sunshine and evaporation at Meerut and sunshine together with soil temperature at Varanasi. 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