Effect of Disc Harrow on the Soil Disturbance Area and Its Prediction and Optimization Using the Artificial Neural Network (ANN) and Response Surface Methodology (RSM)

Effect of Disc Harrow on the Soil Disturbance Area and Its Prediction and Optimization Using the Artificial Neural Network (ANN) and Response Surface Methodology (RSM) | 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 Effect of Disc Harrow on the Soil Disturbance Area and Its Prediction and Optimization Using the Artificial Neural Network (ANN) and Response Surface Methodology (RSM) Hossein Shaebani Sheshpoli, Mohammad Askari, Davood Kalantari This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8350859/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Apr, 2026 Read the published version in Scientific Reports → Version 1 posted 13 You are reading this latest preprint version Abstract Purpose The purpose of this study is to investigate the effects of forward speed, soil moisture content, disc type and disc gang angle on soil disturbance area caused by a four-disc harrow in a soil bin. Moreover, the study aims to predict and optimize the soil disturbance area with considering the input variables to obtain the goals of conservation tillage. Methods The input variables included forward speed (6.43 and 13.15 m/min), soil moisture content (5.37% and 13.25% (db)), disc type (plain and notched), and disc gang angle (0, 15 and 30°). Output variable was soil disturbance area which was measured using profile meter. Tests data were used to develop the regression, artificial neural network (ANN), and response surface methodology (RSM) models and their accuracy were compared. Furthermore, RSM approach was used for optimization process. Results Results indicated that soil disturbance area was significantly affected by disc gang angle (P<0.01), the interaction between moisture and angle (P<0.05), and speed and angle (P<0.01). Increasing the angle from 0 to 15 and 30° substantially enhanced disturbance area (115.1, 222.1, and 337.7 cm², respectively). Regression, ANN and RSM models predicted the disturbance area of notched discs with higher accuracy (R 2 =0.8891, 0.9666 and 0.9696, respectively) than plain discs (R 2 =0.7747, 0.9356 and 0.8826, respectively). The optimization process for disturbance area were obtained 280.814 and 295.710 cm 2 for equal moisture content of 9.31%, forward speed of 8.82 and 7.282 m/min and disc gang angle of 22.57 and 23.935° with equal desirability of 1.000 for plain and notched discs, respectively. Conclusion Among the input variables under investigation, the angle of the plate group was the most effective on soil disturbance area. The best studied prediction approach was RSM for disturbance area of notched discs with highest R 2 (0.9696). The obtained advantages of RSM approach relative to ANN and regression ones in this project are listed as higher accuracy in prediction of soil disturbance area, 3D surface curves in RSM output help readers to better understand the changes in the output parameter under the influence of the input parameters, they can also help researchers to obtain the output parameter in the unmeasured input parameters. Moreover, the optimization process could be done only using RSM. The RSM approach was able to obtain the optimal values of the input variables with a very high desirability (1.000) in order to idealize the soil disturbance rate. Physical sciences/Engineering Earth and environmental sciences/Environmental sciences ANN disc harrow disturbance area RSM soil bin tillage Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 27 Apr, 2026 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 25 Dec, 2025 Reviews received at journal 22 Dec, 2025 Reviews received at journal 21 Dec, 2025 Reviews received at journal 21 Dec, 2025 Reviewers agreed at journal 19 Dec, 2025 Reviewers agreed at journal 19 Dec, 2025 Reviewers agreed at journal 19 Dec, 2025 Reviewers agreed at journal 19 Dec, 2025 Reviewers invited by journal 19 Dec, 2025 Editor invited by journal 17 Dec, 2025 Editor assigned by journal 16 Dec, 2025 Submission checks completed at journal 16 Dec, 2025 First submitted to journal 13 Dec, 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. 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-8350859","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":563614155,"identity":"ef961a39-d2f8-4289-9f49-c81caedbad41","order_by":0,"name":"Hossein Shaebani Sheshpoli","email":"","orcid":"","institution":"Sari Agricultural Sciences and Natural Resources University (SANRU)","correspondingAuthor":false,"prefix":"","firstName":"Hossein","middleName":"Shaebani","lastName":"Sheshpoli","suffix":""},{"id":563614156,"identity":"8750d897-03c5-4740-bf9d-0e04b17d9b94","order_by":1,"name":"Mohammad 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(RSM)","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":"ANN, disc harrow, disturbance area, RSM, soil bin, tillage","lastPublishedDoi":"10.21203/rs.3.rs-8350859/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8350859/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe purpose of this study is to investigate the effects of forward speed, soil moisture content, disc type and disc gang angle on soil disturbance area caused by a four-disc harrow in a soil bin. Moreover, the study aims to predict and optimize the soil disturbance area with considering the input variables to obtain the goals of conservation tillage.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe input variables included forward speed (6.43 and 13.15 m/min), soil moisture content (5.37% and 13.25% (db)), disc type (plain and notched), and disc gang angle (0, 15 and 30°). Output variable was soil disturbance area which was measured using profile meter. Tests data were used to develop the regression, artificial neural network (ANN), and response surface methodology (RSM) models and their accuracy were compared. Furthermore, RSM approach was used for optimization process.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResults indicated that soil disturbance area was significantly affected by disc gang angle (P\u0026lt;0.01), the interaction between moisture and angle (P\u0026lt;0.05), and speed and angle (P\u0026lt;0.01). Increasing the angle from 0 to 15 and 30° substantially enhanced disturbance area (115.1, 222.1, and 337.7 cm², respectively). Regression, ANN and RSM models predicted the disturbance area of notched discs with higher accuracy (R\u003csup\u003e2\u003c/sup\u003e=0.8891, 0.9666 and 0.9696, respectively) than plain discs (R\u003csup\u003e2\u003c/sup\u003e=0.7747, 0.9356 and 0.8826, respectively). The optimization process for disturbance area were obtained 280.814 and 295.710 cm\u003csup\u003e2\u003c/sup\u003e for equal moisture content of 9.31%, forward speed of 8.82 and 7.282 m/min and disc gang angle of 22.57 and 23.935° with equal desirability of 1.000 for plain and notched discs, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong the input variables under investigation, the angle of the plate group was the most effective on soil disturbance area. The best studied prediction approach was RSM for disturbance area of notched discs with highest R\u003csup\u003e2\u003c/sup\u003e (0.9696). The obtained advantages of RSM approach relative to ANN and regression ones in this project are listed as higher accuracy in prediction of soil disturbance area, 3D surface curves in RSM output help readers to better understand the changes in the output parameter under the influence of the input parameters, they can also help researchers to obtain the output parameter in the unmeasured input parameters. Moreover, the optimization process could be done only using RSM. The RSM approach was able to obtain the optimal values of the input variables with a very high desirability (1.000) in order to idealize the soil disturbance rate.\u003c/p\u003e","manuscriptTitle":"Effect of Disc Harrow on the Soil Disturbance Area and Its Prediction and Optimization Using the Artificial Neural Network (ANN) and Response Surface Methodology (RSM)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-22 18:14:28","doi":"10.21203/rs.3.rs-8350859/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-26T04:28:24+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-22T19:02:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-22T04:30:27+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-21T10:45:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"99164472996283433767216656803329489747","date":"2025-12-19T16:22:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"70089597516428265543302225582936391791","date":"2025-12-19T15:45:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"178308908347627522581909969931876063528","date":"2025-12-19T15:31:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"89417863277762008643916355489995840868","date":"2025-12-19T15:20:21+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-19T15:11:48+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-17T12:43:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-16T14:57:31+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-16T14:53:17+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-12-13T07:04:56+00:00","index":"","fulltext":""}],"status":"published","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}}],"origin":"","ownerIdentity":"2c6a4d4d-23c7-43d3-a821-3da88e439e71","owner":[],"postedDate":"December 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":60017123,"name":"Physical sciences/Engineering"},{"id":60017124,"name":"Earth and environmental sciences/Environmental sciences"}],"tags":[],"updatedAt":"2026-05-04T15:59:21+00:00","versionOfRecord":{"articleIdentity":"rs-8350859","link":"https://doi.org/10.1038/s41598-026-49115-9","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-04-27 15:57:23","publishedOnDateReadable":"April 27th, 2026"},"versionCreatedAt":"2025-12-22 18:14:28","video":"","vorDoi":"10.1038/s41598-026-49115-9","vorDoiUrl":"https://doi.org/10.1038/s41598-026-49115-9","workflowStages":[]},"version":"v1","identity":"rs-8350859","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8350859","identity":"rs-8350859","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}