Multispecies weed mapping using deep learning on UAV imagery for SSWM in maize and tomato

Multispecies weed mapping using deep learning on UAV imagery for SSWM in maize and tomato | 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 Multispecies weed mapping using deep learning on UAV imagery for SSWM in maize and tomato Gustavo Adolfo Mesías-Ruiz, Irene Borra-Serrano, José Dorado, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7759568/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Dec, 2025 Read the published version in Precision Agriculture → Version 1 posted You are reading this latest preprint version Abstract Accurate identification and mapping of multiple weed species at early growth stages is a critical step toward operational site-specific weed management (SSWM), yet most UAV-based studies have so far been limited to broad weed categories or single dominant species. This study evaluated the potential of deep learning models, including three convolutional neural networks (Inception-ResNet-v2, EfficientNet-B0, YOLOv8) and two Vision Transformers (ViT-Base, Swin-T), to classify, detect and map nine common weed species in maize and tomato fields using UAV-based RGB imagery. The two best-performing classifiers were then implemented in object detection frameworks (YOLOv8m and DETA), and species-specific treatment maps were generated using adaptive economic weed thresholds applied to gridded density weed data. Classification results showed that Swin-T and YOLOv8 achieved the highest metrics, with weighted F1-scores of 98.1% and 97.0%, respectively. Next, the YOLOv8m provided the most accurate and efficient detection, with a mean Average Precision of 0.93 and recall of 0.94, while substantially reducing inference time. The multispecies treatment maps revealed over 70% of weed-free areas, indicating the potential benefits of cost-saving approaches compared to uniform full-field treatments, providing valuable inputs for decision support systems and smart sprayers to gradually advance SSWM for a more selective, efficient and sustainable weed control. remote sensing site-specific weed management convolutional neural networks (CNN) vision transformers (ViT) object detection Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 27 Dec, 2025 Read the published version in Precision Agriculture → 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-7759568","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":531682932,"identity":"5f67f8cc-31e8-4bb6-9752-a2066acb6ce0","order_by":0,"name":"Gustavo Adolfo Mesías-Ruiz","email":"","orcid":"","institution":"Institute of Agricultural Sciences, Spanish National Research Council (CSIC)","correspondingAuthor":false,"prefix":"","firstName":"Gustavo","middleName":"Adolfo","lastName":"Mesías-Ruiz","suffix":""},{"id":531682933,"identity":"8d036ec9-abc7-4a67-8ecf-08c7922ff375","order_by":1,"name":"Irene Borra-Serrano","email":"","orcid":"","institution":"Institute of Agricultural Sciences, Spanish National Research Council (CSIC)","correspondingAuthor":false,"prefix":"","firstName":"Irene","middleName":"","lastName":"Borra-Serrano","suffix":""},{"id":531682934,"identity":"450f24f4-794d-477d-9c72-2392ea56d6a6","order_by":2,"name":"José Dorado","email":"","orcid":"","institution":"Institute of Agricultural Sciences, Spanish National Research Council (CSIC)","correspondingAuthor":false,"prefix":"","firstName":"José","middleName":"","lastName":"Dorado","suffix":""},{"id":531682935,"identity":"d7228d60-6eba-4df1-8d18-1d28895e6239","order_by":3,"name":"Ana Isabel de Castro","email":"","orcid":"","institution":"National Institute for Agricultural and Food Research and Technology (INIA), Spanish National Research Council (CSIC)","correspondingAuthor":false,"prefix":"","firstName":"Ana","middleName":"Isabel","lastName":"de Castro","suffix":""},{"id":531682936,"identity":"d8bdc9d5-62de-4598-8440-d20bc1faf566","order_by":4,"name":"José Manuel Peña","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0UlEQVRIiWNgGAWjYBACxgYwZcMD4RoQryWNBC1QcJh4pQzM084efFxQc16Gv/0A48cfBXYM/PwHCDhsdl6y8Yxjt3kkziQwS/MYJDNIzkggpCXHTJqH7TaPAUMCGzODwQEGgxsEHAbUYv6b5985HgP+B2yMP4Ba7M8TdFiOGTNv2wEeA4kENgYekC0MBB2WlyzN25fMI3HjYTPIL0AGAS2Gs3MPfub5ZmfP35988OOPP3Zy/P0EHGbYwAO3sAFE8uBUCgPyRKgZBaNgFIyCkQ4Af1o5eRN8GUsAAAAASUVORK5CYII=","orcid":"","institution":"Institute of Agricultural Sciences, Spanish National Research Council (CSIC)","correspondingAuthor":true,"prefix":"","firstName":"José","middleName":"Manuel","lastName":"Peña","suffix":""}],"badges":[],"createdAt":"2025-10-01 12:38:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7759568/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7759568/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11119-025-10309-2","type":"published","date":"2025-12-27T15:58:07+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":93981693,"identity":"3c7cc88f-73c6-42b6-a97f-b83e0e4e7e9c","added_by":"auto","created_at":"2025-10-21 03:01:00","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2918728,"visible":true,"origin":"","legend":"","description":"","filename":"PaperPRAGv1submitted.docx","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/0d9db93f1e18ecd9066bd1a3.docx"},{"id":93981686,"identity":"54fe5d3f-fa56-4ef7-b68c-e24ea65fff6b","added_by":"auto","created_at":"2025-10-21 03:01:00","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":6921,"visible":true,"origin":"","legend":"","description":"","filename":"30095d8eb08f4855b06b9dd1c226eec2.json","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/8bddf12a708d167de01f523a.json"},{"id":93981709,"identity":"8b77e6d4-5ec3-47b0-b8f7-105f8e22c1a9","added_by":"auto","created_at":"2025-10-21 03:01:01","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":227715,"visible":true,"origin":"","legend":"","description":"","filename":"30095d8eb08f4855b06b9dd1c226eec21enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/ac9c9663b6f5a912806ed99b.xml"},{"id":93981687,"identity":"422985cf-1e3a-472c-87a4-73aa4be89e32","added_by":"auto","created_at":"2025-10-21 03:01:00","extension":"jpeg","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":317542,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/45c08b1f8c6768f00a8cffd6.jpeg"},{"id":93981690,"identity":"64a33201-c1a0-4fcd-bb2b-ec8d5c1b9913","added_by":"auto","created_at":"2025-10-21 03:01:00","extension":"jpeg","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":199475,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage10.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/7bc2b9cce3380bc25e3217fa.jpeg"},{"id":93982291,"identity":"2a0608c9-b3b8-4ee2-891e-eef1a854740e","added_by":"auto","created_at":"2025-10-21 03:17:01","extension":"jpeg","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":687912,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/721f65900f462df2647d05bc.jpeg"},{"id":93982154,"identity":"172e80b1-31a4-43a9-8b58-66ca34fb67ed","added_by":"auto","created_at":"2025-10-21 03:09:00","extension":"jpeg","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":416808,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/8dddaff73c43860888e22181.jpeg"},{"id":93982157,"identity":"8d182de3-1ab2-4ed2-8465-9ba640c3f361","added_by":"auto","created_at":"2025-10-21 03:09:00","extension":"jpeg","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":95292,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/c5999063b54efc1dd22a1c6f.jpeg"},{"id":93982289,"identity":"ae989d36-8a85-4702-839e-0bda6465dcf6","added_by":"auto","created_at":"2025-10-21 03:17:00","extension":"jpeg","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":135672,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/ec96a4f02c34323e5c5a542f.jpeg"},{"id":93982156,"identity":"18271558-e9b9-43c7-acf8-5ea47c45b9fa","added_by":"auto","created_at":"2025-10-21 03:09:00","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":392199,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/2715167e25087f0e813080a6.png"},{"id":93981691,"identity":"9fc8d18b-e349-4f27-856d-016370e14b10","added_by":"auto","created_at":"2025-10-21 03:01:00","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":100751,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/abf3d20c0ef06cc529523bab.png"},{"id":93981707,"identity":"91de1fb1-0b82-4558-b2ba-1b78290ceb54","added_by":"auto","created_at":"2025-10-21 03:01:01","extension":"jpeg","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":362804,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage8.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/168ec4c40f5776d31735faae.jpeg"},{"id":93982290,"identity":"caf8bba4-48e0-4c59-a0bb-a8b16096eafb","added_by":"auto","created_at":"2025-10-21 03:17:00","extension":"jpeg","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":99208,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage9.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/fd4d1575728eeb9cea8a8cca.jpeg"},{"id":93981704,"identity":"6b70c133-5428-4894-8dba-0dc1b1662af8","added_by":"auto","created_at":"2025-10-21 03:01:01","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":44779,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/12aa7f3c6e5625700e23c6d7.png"},{"id":93981699,"identity":"314dd1b5-c424-44df-9368-5fa8fc47a206","added_by":"auto","created_at":"2025-10-21 03:01:00","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":131113,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/90221749a2521672a9b94428.png"},{"id":93982159,"identity":"acc9cc18-d29f-41cf-b603-a1be0701a336","added_by":"auto","created_at":"2025-10-21 03:09:01","extension":"png","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":73890,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/c694ccb1f329558140444ee2.png"},{"id":93982162,"identity":"d837007a-3d7a-4151-99d2-4de46ab200f4","added_by":"auto","created_at":"2025-10-21 03:09:01","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":60297,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/00ac8677ce4a5e913a389fe7.png"},{"id":93982163,"identity":"8f776533-3b74-4781-9cf3-8ebce01bbb2a","added_by":"auto","created_at":"2025-10-21 03:09:01","extension":"png","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":16422,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/8da5b343de269b456b6ad409.png"},{"id":93981697,"identity":"fc49cba5-bd79-4fd6-aa07-d3ee96c816e7","added_by":"auto","created_at":"2025-10-21 03:01:00","extension":"png","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":22836,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/ce8c3a93e6435e69cd61dc1c.png"},{"id":93981701,"identity":"f759315e-979a-46a7-8162-0b48b908f716","added_by":"auto","created_at":"2025-10-21 03:01:01","extension":"png","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":66104,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/a26fe9ed5457d55483a57c8a.png"},{"id":93981695,"identity":"9f2c0c7a-2a78-4ceb-b11e-a7dbf5bcf753","added_by":"auto","created_at":"2025-10-21 03:01:00","extension":"png","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":23114,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/0a0901225dd3ec063cf77792.png"},{"id":93982160,"identity":"2b9bb2e3-7215-40f1-9e3e-42b6b08bcfac","added_by":"auto","created_at":"2025-10-21 03:09:01","extension":"png","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":187745,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/4645b4cfad0e1a307e00b275.png"},{"id":93981694,"identity":"6009ec8f-edaa-4ddf-8efb-10837584240e","added_by":"auto","created_at":"2025-10-21 03:01:00","extension":"png","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":15199,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/b8950f05cd83286aad2f3b49.png"},{"id":93981710,"identity":"fe05158c-f1f3-408a-a6c3-b68456e2e132","added_by":"auto","created_at":"2025-10-21 03:01:01","extension":"xml","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":222453,"visible":true,"origin":"","legend":"","description":"","filename":"30095d8eb08f4855b06b9dd1c226eec21structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/ce151c61bdb1c36e0add2e17.xml"},{"id":93981708,"identity":"94dda2bc-3cda-44c4-905f-cf63766e4180","added_by":"auto","created_at":"2025-10-21 03:01:01","extension":"html","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":243630,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1/eac5bc50daa588b33e22cb97.html"},{"id":99172358,"identity":"b17569a3-aec2-45e2-9f82-6f7e301d0be0","added_by":"auto","created_at":"2025-12-29 16:08:18","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1340152,"visible":true,"origin":"","legend":"","description":"","filename":"PaperPRAGv1submitted.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7759568/v1_covered_6a315bd7-a144-4bd6-a1dd-90d17e23b759.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Multispecies weed mapping using deep learning on UAV imagery for SSWM in maize and tomato","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":"remote sensing, site-specific weed management, convolutional neural networks (CNN), vision transformers (ViT), object detection","lastPublishedDoi":"10.21203/rs.3.rs-7759568/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7759568/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAccurate identification and mapping of multiple weed species at early growth stages is a critical step toward operational site-specific weed management (SSWM), yet most UAV-based studies have so far been limited to broad weed categories or single dominant species. This study evaluated the potential of deep learning models, including three convolutional neural networks (Inception-ResNet-v2, EfficientNet-B0, YOLOv8) and two Vision Transformers (ViT-Base, Swin-T), to classify, detect and map nine common weed species in maize and tomato fields using UAV-based RGB imagery. The two best-performing classifiers were then implemented in object detection frameworks (YOLOv8m and DETA), and species-specific treatment maps were generated using adaptive economic weed thresholds applied to gridded density weed data. Classification results showed that Swin-T and YOLOv8 achieved the highest metrics, with weighted F1-scores of 98.1% and 97.0%, respectively. Next, the YOLOv8m provided the most accurate and efficient detection, with a mean Average Precision of 0.93 and recall of 0.94, while substantially reducing inference time. The multispecies treatment maps revealed over 70% of weed-free areas, indicating the potential benefits of cost-saving approaches compared to uniform full-field treatments, providing valuable inputs for decision support systems and smart sprayers to gradually advance SSWM for a more selective, efficient and sustainable weed control.\u003c/p\u003e","manuscriptTitle":"Multispecies weed mapping using deep learning on UAV imagery for SSWM in maize and tomato","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-21 03:00:55","doi":"10.21203/rs.3.rs-7759568/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":"b8f56026-612c-4eca-8541-70135ee1f392","owner":[],"postedDate":"October 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-29T16:02:09+00:00","versionOfRecord":{"articleIdentity":"rs-7759568","link":"https://doi.org/10.1007/s11119-025-10309-2","journal":{"identity":"precision-agriculture","isVorOnly":false,"title":"Precision Agriculture"},"publishedOn":"2025-12-27 15:58:07","publishedOnDateReadable":"December 27th, 2025"},"versionCreatedAt":"2025-10-21 03:00:55","video":"","vorDoi":"10.1007/s11119-025-10309-2","vorDoiUrl":"https://doi.org/10.1007/s11119-025-10309-2","workflowStages":[]},"version":"v1","identity":"rs-7759568","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7759568","identity":"rs-7759568","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}