Investigating and machine learning predicting the Impact of Nandina domestica Roots on the Unconfined Compressive Strength of unsaturated silty clay

Investigating and machine learning predicting the Impact of Nandina domestica Roots on the Unconfined Compressive Strength of unsaturated silty clay | 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 Investigating and machine learning predicting the Impact of Nandina domestica Roots on the Unconfined Compressive Strength of unsaturated silty clay Masoud Ebrahimi Derakhshan, Mehrab Ramzani, Hamid Reza Razeghi, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7091114/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Jan, 2026 Read the published version in Transportation Infrastructure Geotechnology → Version 1 posted You are reading this latest preprint version Abstract Bio - stabilization of soil using natural vegetation offers a sustainable and cost-effective approach to slope management and erosion control. Furthermore, soft computing technologies are necessary since experimental research is often challenging, and time consuming. This article discusses the modelling and the performance of nonlinear and Random Forest (RF) model for predict UCS ultimate stress and trajectory of root-soil stress-strain. Nandina domestica is particularly promising due to its hardiness and low maintenance requirements, making it an economical and sustainable option for soil bio-stabilization. Using compressive strength, the effects of moisture content, root weight density (RWD), and root diameter (RD) on soil reinforcement were evaluated. 144 silty clay soil samples reinforced with four RWD (1, 2, 3 and 4 gr/cm 3 ) and three RD (1, 2 and 3 mm) in four moisture conditions (20, 25, 30, and 35%) was considered to determine the UCS. The proposed nonlinear model demonstrated acceptable predictive accuracy (R² = 0.84) with RMSE=8.7 kPa and MAE=7.13 kPa values predicted the contribution of Nandina domestica roots to soil ultimate UCS reinforcement. The data was split into three sections for the development of the RF model: the training data set (70%), the testing data set (15%) and the testing unseen data set (15%). The proposed model accurately predicted the trajectory of unknown data root-soil stress-strain and contribution of Nandina domestica roots to soil reinforcement, exhibiting strong performance with R² = 0.97, RMSE = 3 kPa, and MAE = 1.8 kPa. Root-soil composite Unconfined compressive strength Random Forest Nandina domestica Roots Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 10 Jan, 2026 Read the published version in Transportation Infrastructure Geotechnology → 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-7091114","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":492763332,"identity":"b56a6b0e-f9ba-4220-ae1d-2bdcec52be64","order_by":0,"name":"Masoud Ebrahimi Derakhshan","email":"data:image/png;base64,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","orcid":"","institution":"Iran University of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Masoud","middleName":"Ebrahimi","lastName":"Derakhshan","suffix":""},{"id":492763334,"identity":"8624e77e-bc21-4942-a10f-d6ac49b9ee65","order_by":1,"name":"Mehrab Ramzani","email":"","orcid":"","institution":"Iran University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Mehrab","middleName":"","lastName":"Ramzani","suffix":""},{"id":492763335,"identity":"e5518f87-89cb-48fa-870e-fb2f30a1678c","order_by":2,"name":"Hamid Reza Razeghi","email":"","orcid":"","institution":"Iran University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Hamid","middleName":"Reza","lastName":"Razeghi","suffix":""},{"id":492763338,"identity":"025491e1-b6d5-4a67-a164-7a8020c4f6e3","order_by":3,"name":"Jaber Mamaghanian","email":"","orcid":"","institution":"Iran University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Jaber","middleName":"","lastName":"Mamaghanian","suffix":""}],"badges":[],"createdAt":"2025-07-10 09:08:40","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7091114/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7091114/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s40515-025-00776-5","type":"published","date":"2026-01-10T15:58:03+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":100069471,"identity":"a6370d15-be77-4a2d-941d-86ed911734f8","added_by":"auto","created_at":"2026-01-12 16:14:32","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":750793,"visible":true,"origin":"","legend":"","description":"","filename":"ManuscriptAbstractTablesFigures2025.8.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7091114/v1_covered_e5e51e05-575f-4aeb-bc0c-5205fb39a48f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Investigating and machine learning predicting the Impact of Nandina domestica Roots on the Unconfined Compressive Strength of unsaturated silty clay","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"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":"Root-soil composite, Unconfined compressive strength, Random Forest, Nandina domestica Roots","lastPublishedDoi":"10.21203/rs.3.rs-7091114/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7091114/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBio\u003cstrong\u003e-\u003c/strong\u003estabilization of soil using natural vegetation offers a sustainable and cost-effective approach to slope management and erosion control. Furthermore, soft computing technologies are necessary since experimental research is often challenging, and time consuming. This article discusses the modelling and the performance of nonlinear and Random Forest (RF) model for predict UCS ultimate stress and trajectory of root-soil stress-strain. \u003cem\u003eNandina domestica\u003c/em\u003e is particularly promising due to its hardiness and low maintenance requirements, making it an economical and sustainable option for soil bio-stabilization. Using compressive strength, the effects of moisture content, root weight density (RWD), and root diameter (RD) on soil reinforcement were evaluated. 144 silty clay soil samples reinforced with four RWD (1, 2, 3 and 4 gr/cm\u003csup\u003e3\u003c/sup\u003e) and three RD (1, 2 and 3 mm) in four moisture conditions (20, 25, 30, and 35%) was considered to determine the UCS. The proposed nonlinear model demonstrated acceptable predictive accuracy (R² = 0.84) with RMSE=8.7 kPa and MAE=7.13 kPa values predicted the contribution of Nandina domestica roots to soil ultimate UCS reinforcement. The data was split into three sections for the development of the RF model: the training data set (70%), the testing data set (15%) and the testing unseen data set (15%). The proposed model accurately predicted the trajectory of unknown data root-soil stress-strain and contribution of Nandina domestica roots to soil reinforcement, exhibiting strong performance with R² = 0.97, RMSE = 3 kPa, and MAE = 1.8 kPa.\u003c/p\u003e","manuscriptTitle":"Investigating and machine learning predicting the Impact of Nandina domestica Roots on the Unconfined Compressive Strength of unsaturated silty clay","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-31 10:53:59","doi":"10.21203/rs.3.rs-7091114/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":"3448a306-ea18-47f7-a86f-f2ef8d3ca4de","owner":[],"postedDate":"July 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-12T16:07:51+00:00","versionOfRecord":{"articleIdentity":"rs-7091114","link":"https://doi.org/10.1007/s40515-025-00776-5","journal":{"identity":"transportation-infrastructure-geotechnology","isVorOnly":false,"title":"Transportation Infrastructure Geotechnology"},"publishedOn":"2026-01-10 15:58:03","publishedOnDateReadable":"January 10th, 2026"},"versionCreatedAt":"2025-07-31 10:53:59","video":"","vorDoi":"10.1007/s40515-025-00776-5","vorDoiUrl":"https://doi.org/10.1007/s40515-025-00776-5","workflowStages":[]},"version":"v1","identity":"rs-7091114","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7091114","identity":"rs-7091114","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}