Marine Fish Production in Odisha: A Comparative Analysis of ARIMA and Holt's Linear Trend Models for Forecasting and Production Instability

Marine Fish Production in Odisha: A Comparative Analysis of ARIMA and Holt's Linear Trend Models for Forecasting and Production Instability | 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 Marine Fish Production in Odisha: A Comparative Analysis of ARIMA and Holt's Linear Trend Models for Forecasting and Production Instability Samiran Mukherjee, Neha Wajahat Qureshi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5756556/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 The marine fish production sector of Odisha plays a significant role in the India's fisheries sector, accounting for 4.80% of the nation's marine fish output in 2022–2023. This study aims to investigate the trends, growth patterns, and instability of marine fish production in Odisha from 1990-91 to 2022-23 and forecast production for upcoming years. The annual time series data of marine fish production of Odisha was obtained. Marine fish production exhibited a gradual increase, but the overall CGR remained modest (1.56%). Exponential Trend method was used to fit the historical production data (R 2 = 0.56). While ARIMA (0,1,0) and HLT models both were suitable for forecasting, HLT model achieved higher accuracy (93%). The study investigates district-wise growth patterns and instabilities, identifying Kendrapara as exhibiting significant instability in recent years. The analysis highlights the disparities in production, with Balasore, Jagatsinghpur, and Puri emerging as major contributors. Instability analysis using Coefficient of Variation (C.V.), Coppock’s Instability Index (CII), Cuddy-Delle Valle Index (CDVI) revealed Kendrapara’s instability in marine fish production. Kendrapara stands out for its notable instability, attributed to a combination of environmental, socio-economic, and government regulation-related factors such as cyclones, limited infrastructures, and fishing restrictions. Challenges such as underreporting and market constraints pose significant barriers to harnessing the potential of marine fisheries in Odisha. The study highlights need for improved production strategies in Odisha’s marine fisheries sector and places emphasis on determining the factors affecting state's marine fish landings ensuring sustainable growth and helping shape state and district-wise policy decisions on infrastructure development. Odisha Marine fish production Growth Trend Time Series Analysis Instability Analysis 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-5756556","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":398820050,"identity":"cba019da-5fa7-4e01-ba6e-d47c3022b289","order_by":0,"name":"Samiran Mukherjee","email":"","orcid":"","institution":"ICAR–Central Institute of Fisheries Education","correspondingAuthor":false,"prefix":"","firstName":"Samiran","middleName":"","lastName":"Mukherjee","suffix":""},{"id":398820052,"identity":"1729e010-ba7a-46bd-b2bb-e165b4256aa4","order_by":1,"name":"Neha Wajahat Qureshi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYFACHiCuYOBhb4CweYjUcoaBh+cASVoY24AUVAthYM7ee/DD23l2MkCXMT5428YgY05Ii2XPuWTJuduSeYAuYzac28bAY9lAQIvBjRwDad5tB3jsJRLYpHmBWgwOENJy/43xb945B3h45B+w/yZOyw0eM2neBqAWCQY2ZuK0nMkxs5xzDOSXxGbJOeckiNBy/IzxjTc1dvY87IcPfnhTZmNPUAsYQKKDsQFISBCjnoHIGBwFo2AUjIKRCwCTdTcfR6sGNgAAAABJRU5ErkJggg==","orcid":"","institution":"ICAR–Central Institute of Fisheries Education","correspondingAuthor":true,"prefix":"","firstName":"Neha","middleName":"Wajahat","lastName":"Qureshi","suffix":""}],"badges":[],"createdAt":"2025-01-03 08:23:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5756556/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5756556/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81470642,"identity":"bd47b326-fd98-4891-9156-282567c817c5","added_by":"auto","created_at":"2025-04-27 09:16:50","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":813088,"visible":true,"origin":"","legend":"","description":"","filename":"OdishaMarineFishProductionSamiranMukherjeeRevised07.01.25.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5756556/v1_covered_2b192324-a04b-41d6-a9b3-32a2372aed22.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Marine Fish Production in Odisha: A Comparative Analysis of ARIMA and Holt's Linear Trend Models for Forecasting and Production Instability","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":"Odisha, Marine fish production, Growth Trend, Time Series Analysis, Instability Analysis","lastPublishedDoi":"10.21203/rs.3.rs-5756556/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5756556/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe marine fish production sector of Odisha plays a significant role in the India's fisheries sector, accounting for 4.80% of the nation's marine fish output in 2022\u0026ndash;2023. This study aims to investigate the trends, growth patterns, and instability of marine fish production in Odisha from 1990-91 to 2022-23 and forecast production for upcoming years. The annual time series data of marine fish production of Odisha was obtained. Marine fish production exhibited a gradual increase, but the overall CGR remained modest (1.56%). Exponential Trend method was used to fit the historical production data (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.56). While ARIMA (0,1,0) and HLT models both were suitable for forecasting, HLT model achieved higher accuracy (93%). The study investigates district-wise growth patterns and instabilities, identifying Kendrapara as exhibiting significant instability in recent years. The analysis highlights the disparities in production, with Balasore, Jagatsinghpur, and Puri emerging as major contributors. Instability analysis using Coefficient of Variation (C.V.), Coppock\u0026rsquo;s Instability Index (CII), Cuddy-Delle Valle Index (CDVI) revealed Kendrapara\u0026rsquo;s instability in marine fish production. Kendrapara stands out for its notable instability, attributed to a combination of environmental, socio-economic, and government regulation-related factors such as cyclones, limited infrastructures, and fishing restrictions. Challenges such as underreporting and market constraints pose significant barriers to harnessing the potential of marine fisheries in Odisha. The study highlights need for improved production strategies in Odisha\u0026rsquo;s marine fisheries sector and places emphasis on determining the factors affecting state's marine fish landings ensuring sustainable growth and helping shape state and district-wise policy decisions on infrastructure development.\u003c/p\u003e","manuscriptTitle":"Marine Fish Production in Odisha: A Comparative Analysis of ARIMA and Holt's Linear Trend Models for Forecasting and Production Instability","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-09 02:11:23","doi":"10.21203/rs.3.rs-5756556/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":"8d9a7cb2-4c75-4526-915d-3b1445725360","owner":[],"postedDate":"January 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-27T09:08:40+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-09 02:11:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5756556","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5756556","identity":"rs-5756556","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}