Profile Distribution and Interrelationships of Soil Physico-Chemical Properties under Major Orchards in Varanasi Region, India

preprint OA: closed
Full text JSON View at publisher
Full text 10,348 characters · extracted from preprint-html · click to expand
Profile Distribution and Interrelationships of Soil Physico-Chemical Properties under Major Orchards in Varanasi Region, India | 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 Profile Distribution and Interrelationships of Soil Physico-Chemical Properties under Major Orchards in Varanasi Region, India Fsaha Mebrahtu Gebru This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9563161/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 In the Varanasi region of Uttar Pradesh, the study evaluated the distribution and correlations of soil physico-chemical parameters under major orchard systems. Ninety soil samples were taken at five depths (0–15 to 90–120 cm) from six orchards (mango, guava, citrus, bael, ber, and pomegranate). Physical characteristics (bulk density, particle density, porosity, water-holding capacity), chemical characteristics (pH, electrical conductivity, organic carbon, macronutrients, and secondary nutrients), and DTPA-extractable micronutrients (Fe, Mn, Zn, and Cu) were all examined in the samples. The findings revealed distinct vertical trends: whereas organic carbon, porosity, and nutrient availability decreased with depth, bulk density rose. In deeper levels, the pH of the soil changed from slightly acidic at the surface to neutral to slightly alkaline. While bulk density had a negative impact on fertility, correlation analysis revealed that organic carbon was a crucial regulator of nutritional availability. Strong connections between nutrients and organic matter were shown by cluster analysis, which divided characteristics into three clusters. PCA verified that the primary causes of variability were fertility factors and organic matter. Supported by SFI and SEF, mango and pomegranate orchards demonstrated more fertility than citrus and bael. Horticulture Soil physico-chemical properties Orchard systems Nutrient stratification Correlation analysis Cluster analysis 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-9563161","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":631615676,"identity":"655820fc-4686-4a73-b56a-9597fa039eeb","order_by":0,"name":"Fsaha Mebrahtu Gebru","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2klEQVRIiWNgGAWjYDAC9oaEDwwMBxj4QZyEAmK08Bx4OAOkRbIBpMWAGC0SiRAtBgdAPGK06DYkJzb+qLkjb3x+deKHBwYM8vxiB/BrMTtwLLGZ59gzw2033m6WADrMcObsBAJaDvakP2ZgO8y47cbZDSAtCQa3CWk5zP+x8ce/w/abZ5zd/IM4LccYEht42w4nbuDv3UakLWcYEpt5+w4nz7jBu80iwUCCCL/cfwAMsW+Hbfv7z26++aPCRp5fmoAWBJAAq5QgVjkI8B8gRfUoGAWjYBSMJAAAnu1RK8I/RroAAAAASUVORK5CYII=","orcid":"","institution":"Raya University","correspondingAuthor":true,"prefix":"","firstName":"Fsaha","middleName":"Mebrahtu","lastName":"Gebru","suffix":""}],"badges":[],"createdAt":"2026-04-29 09:01:42","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-9563161/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9563161/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108182999,"identity":"a02e6b6f-bf7c-4bac-a324-43ad2b2da838","added_by":"auto","created_at":"2026-04-30 08:59:44","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1105481,"visible":true,"origin":"","legend":"","description":"","filename":"FinalDraftR1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9563161/v1_covered_b64a21e8-dd87-408c-b8fd-6de2f2d28f16.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eProfile Distribution and Interrelationships of Soil Physico-Chemical Properties under Major Orchards in Varanasi Region, India\u003c/strong\u003e\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Raya University","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":"Soil physico-chemical properties, Orchard systems, Nutrient stratification, Correlation analysis, Cluster analysis","lastPublishedDoi":"10.21203/rs.3.rs-9563161/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9563161/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn the Varanasi region of Uttar Pradesh, the study evaluated the distribution and correlations of soil physico-chemical parameters under major orchard systems. Ninety soil samples were taken at five depths (0–15 to 90–120 cm) from six orchards (mango, guava, citrus, bael, ber, and pomegranate). Physical characteristics (bulk density, particle density, porosity, water-holding capacity), chemical characteristics (pH, electrical conductivity, organic carbon, macronutrients, and secondary nutrients), and DTPA-extractable micronutrients (Fe, Mn, Zn, and Cu) were all examined in the samples. The findings revealed distinct vertical trends: whereas organic carbon, porosity, and nutrient availability decreased with depth, bulk density rose. In deeper levels, the pH of the soil changed from slightly acidic at the surface to neutral to slightly alkaline. While bulk density had a negative impact on fertility, correlation analysis revealed that organic carbon was a crucial regulator of nutritional availability. Strong connections between nutrients and organic matter were shown by cluster analysis, which divided characteristics into three clusters. PCA verified that the primary causes of variability were fertility factors and organic matter. Supported by SFI and SEF, mango and pomegranate orchards demonstrated more fertility than citrus and bael.\u003c/p\u003e","manuscriptTitle":"Profile Distribution and Interrelationships of Soil Physico-Chemical Properties under Major Orchards in Varanasi Region, India","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-30 07:03:37","doi":"10.21203/rs.3.rs-9563161/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","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}}],"origin":"","ownerIdentity":"c7c0343e-a2cf-42d1-9df3-84e874c74e93","owner":[],"postedDate":"April 30th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":67229102,"name":"Horticulture"}],"tags":[],"updatedAt":"2026-04-30T07:03:38+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-30 07:03:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9563161","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9563161","identity":"rs-9563161","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: preprint-html

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2026) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

europepmc
last seen: 2026-05-20T01:45:00.602351+00:00