{"datasetrec":{"DasID":7855,"Acronym":null,"StandardTitle":"RGB-statistics derived from Nile red-stained reference plastics for the construction of the PIM (Polymer Identification Model)","OrigTitle":null,"OrigTitleLangID":null,"OrigTitleLangCode":null,"OrigTitleLang":null,"OrigTitleLangNL":null,"VersionName":null,"ContactEmail":null,"VersionDate":null,"VersionDay":null,"VersionMonth":null,"VersionYear":null,"SizeReference":null,"EngAbstract":"Dataset containing RGB-statistics extracted from photographed fluorescent reference plastics stained with Nile red. The most abundantly produced plastic polymers worldwide considered for this dataset. The spectral data was used to construct a supervised machine learning model that allows to accurately identify the polymer types microplastics belong to, in a cost- and time-efficient way.","EngDescr":"The dataset was built to train and validate the ‘Polymer Identification Model’ (PIM) in R and contains Red, Green and Blue (RGB) statistics extracted from Nile red-stained reference plastics (50-1200 μm) photographed under three different microscope filters (UV: Filter System A S, BP 340-380 nm; blue: Filter System I3 S, BP 450-490 nm; and green: Filter system N2.1 S, BP 515-560 nm) (LEICA DM 1000). Image analysis to extract all RGB-values was performed using a macro in ImageJ. The supervised machine learning model (CART algorithm) trained by and validated with this dataset predicts with high accuracy the polymer types microplastics belong to, in a cost- and time-efficient way. RGB statistics of the most abundantly produced plastic polymers worldwide were compiled into the dataset. The statistics itself were calculated per reference particle as the 10th, 50th and 90th percentile as well as the mean of each of the three different color components extracted from all pixels laying along the maximum Feret diameter of that photographed particle. The dataset contains RGB-statistics calculated through image analysis of 210 plastic particles belonging to seven polymer types (Nylon, PE, PET, PP, PS, PUR and PVC) (30 particles/polymer type), where 168 particles (1/4) were randomly selected and used to serve as training data (24 particles/polymer) (worksheet tab ‘training data’), while the remaining 42 particles (1/5) were kept as independent validation data (6 particles/polymer type) (worksheet tab ‘training data’).","OrigAbstract":null,"OrigDescr":null,"Comments":null,"ReleaseDate":null,"ReleaseDate0":null,"OrigDescrLang":null,"EmbargoDate":null,"OrigDescrLangNL":null,"OrigLangCode":null,"OrigLangCodeExtended":null,"OrigLangID":null,"DescrCompFlag":0,"DescrTransFlag":0,"Citation":"Meyers, N.; Catarino, A.I.; Declercq, A.M.; Brenan, A.; Devriese, L.; Vandegehuchte, M.; De Witte, B.; Janssen, C.; Everaert, G.; Flanders Marine Institute (VLIZ); Flanders Research Institute for Agriculture, Fisheries and Food (ILVO); Ghent University Laboratory for Environmental Toxicology (GhEnToxLab): Belgium; (2021): RGB-statistics derived from Nile red-stained reference plastics for the construction of the PIM (Polymer Identification Model). Marine Data Archive.","AccessConstraints":null,"UDate":"2021-09-28","CDate":"2021-08-23","CurrencyDate":null,"RevisionDate":null,"DateLastModified":{"date":"2026-05-23 01:39:24.004480","timezone_type":1,"timezone":"+02:00"},"CheckedFlag":0,"PublicFlag":1,"VlizCoreFlag":1,"MarineFlag":1,"FreshFlag":1,"BrackishFlag":1,"TerrestrialFlag":0,"StatusID":1,"DasType":"Data","DasTypeID":1,"DasOrigin":"Research: lab experiment","Progress":"Completed","AccessConstraint":"Attribution (CC BY)","AccConstrEN":"Attribution (CC BY)","AccConstrDisplay":"\"Creative This dataset is licensed under a Creative Commons Attribution 4.0 International License.","License":"https://creativecommons.org/licenses/by/4.0/","AccConstrDescription":"This license lets others distribute, remix, tweak, and build upon your work, even commercially, as long as they credit you for the original creation. This is the most accommodating of licenses offered. Recommended for maximum dissemination and use of licensed materials.","Lineage":null,"AccConID":21},"dois":[{"DOIID":563,"PublicationYear":2021,"DOI":"10.14284/511","Citation":"Meyers, N.; Catarino, A.I.; Declercq, A.M.; Brenan, A.; Devriese, L.; Vandegehuchte, M.; De Witte, B.; Janssen, C.; Everaert, G.; Flanders Marine Institute (VLIZ); Flanders Research Institute for Agriculture, Fisheries and Food (ILVO); Ghent University Laboratory for Environmental Toxicology (GhEnToxLab): Belgium; (2021): RGB-statistics derived from Nile red-stained reference plastics for the construction of the PIM (Polymer Identification Model). Marine Data Archive.","MDAID":"VLIZ_00000311_6152f771e1ab4377315361","Moratorium":0,"MDAURL":"https://mda.vliz.be/directlink.php?fid=VLIZ_00000311_6152f771e1ab4377315361","CurrentDOI":1,"Active":1,"URL":null,"downloadURL":"https://mda.vliz.be/download.php?file=VLIZ_00000311_6152f771e1ab4377315361"}],"spcols":null,"keywords":[{"ThesaurusTerm":"Fluorescence microscopy","ThesTypID":4,"ThesType":"CAB Thesaurus","Code":"48710","Description":null,"OrigThesTerm":"Fluorescence microscopy","DutchTerm":null,"URI":"https://id.cabi.org/cabt/48710","DasKeywordDescr":null},{"ThesaurusTerm":"Machine learning","ThesTypID":2,"ThesType":"CSA Technology Research Database Master Thesaurus","Code":null,"Description":null,"OrigThesTerm":"Machine learning","DutchTerm":null,"URI":null,"DasKeywordDescr":null},{"ThesaurusTerm":"Microplastics","ThesTypID":0,"ThesType":null,"Code":null,"Description":null,"OrigThesTerm":"Microplastics","DutchTerm":"Microplastics","URI":null,"DasKeywordDescr":null},{"ThesaurusTerm":"Polymer identification method","ThesTypID":0,"ThesType":null,"Code":null,"Description":null,"OrigThesTerm":"Polymer identification method","DutchTerm":null,"URI":null,"DasKeywordDescr":null},{"ThesaurusTerm":"RGB colour data","ThesTypID":0,"ThesType":null,"Code":null,"Description":null,"OrigThesTerm":"RGB colour data","DutchTerm":null,"URI":null,"DasKeywordDescr":null}],"parents":[{"DasID":8542,"Acronym":null,"EngAbstract":"This dataset features RGB statistics extracted from Nile red-stained particles, serving to train a 'Plastic Detection Model' and a 'Polymer Identification Model' using supervised machine learning techniques. By accurately discerning between plastic and natural particles, and distinguishing between different plastic polymers, the models facilitate efficient microplastic detection and identification.","License":"https://creativecommons.org/licenses/by/4.0/","StandardTitle":"RGB datasets for machine learning-based microplastic analysis - update","doi":null,"vlizDoi":"10.14284/665"}],"children":null,"othrel":null,"othrelrev":[{"DasID":7856,"Acronym":null,"StandardTitle":"RGB-statistics derived from Nile red-stained reference plastics for the construction of the PDM (Plastics Detection Model)","Relation":"Related Dataset","RelationY":"Related Dataset","RelID":11,"doi":null,"vlizDoi":"10.14284/512"}],"ownerships":[{"OrderNr":1,"Surname":"Meyers","Firstname":"Nelle","Initials":"N.","PerPublicFlag":1,"AdrID":168059,"Email":"nelle.meyers@vliz.be","InsPublicFlag":1,"Acronym":"VLIZ","OrigNameLangCode":"en","OrigNameLangID":15,"FullOrigName":"Flanders Marine Institute","InsOwnerCNT":9,"PersID":30367,"InsID":36,"FullInstitute":"Vlaams Instituut voor de Zee","RoleID":24,"Role":"Contact","OrigName":"Flanders Marine Institute","StandardName":"Vlaams Instituut voor de Zee","FullAcronym":"VLIZ","ORC":"https://orcid.org/0000-0001-9205-6260","ROR":"https://ror.org/0496vr396"},{"OrderNr":2,"Surname":"Meyers","Firstname":"Nelle","Initials":"N.","PerPublicFlag":1,"AdrID":168059,"Email":"nelle.meyers@vliz.be","InsPublicFlag":1,"Acronym":"VLIZ","OrigNameLangCode":"en","OrigNameLangID":15,"FullOrigName":"Flanders Marine Institute","InsOwnerCNT":9,"PersID":30367,"InsID":36,"FullInstitute":"Vlaams Instituut voor de Zee","RoleID":7,"Role":"Co-ordinator","OrigName":"Flanders Marine Institute","StandardName":"Vlaams Instituut voor de Zee","FullAcronym":"VLIZ","ORC":"https://orcid.org/0000-0001-9205-6260","ROR":"https://ror.org/0496vr396"},{"OrderNr":3,"Surname":"Meyers","Firstname":"Nelle","Initials":"N.","PerPublicFlag":1,"AdrID":168059,"Email":"nelle.meyers@vliz.be","InsPublicFlag":1,"Acronym":"VLIZ","OrigNameLangCode":"en","OrigNameLangID":15,"FullOrigName":"Flanders Marine Institute","InsOwnerCNT":9,"PersID":30367,"InsID":36,"FullInstitute":"Vlaams Instituut voor de Zee","RoleID":61,"Role":"Data creator","OrigName":"Flanders Marine Institute","StandardName":"Vlaams Instituut voor de Zee","FullAcronym":"VLIZ","ORC":"https://orcid.org/0000-0001-9205-6260","ROR":"https://ror.org/0496vr396"},{"OrderNr":4,"Surname":"Meyers","Firstname":"Nelle","Initials":"N.","PerPublicFlag":1,"AdrID":167359,"Email":"nelle.meyers@ilvo.vlaanderen.be","InsPublicFlag":1,"Acronym":"ILVO","OrigNameLangCode":"en","OrigNameLangID":15,"FullOrigName":"Flanders Research Institute for Agriculture, Fisheries and Food","InsOwnerCNT":3,"PersID":30367,"InsID":5442,"FullInstitute":"Instituut voor Landbouw-, Visserij- en Voedingsonderzoek","RoleID":61,"Role":"Data creator","OrigName":"Flanders Research Institute for Agriculture, Fisheries and Food","StandardName":"Instituut voor Landbouw-, Visserij- en Voedingsonderzoek","FullAcronym":"ILVO","ORC":"https://orcid.org/0000-0001-9205-6260","ROR":null},{"OrderNr":5,"Surname":"Meyers","Firstname":"Nelle","Initials":"N.","PerPublicFlag":1,"AdrID":null,"Email":null,"InsPublicFlag":1,"Acronym":"GhEnToxLab","OrigNameLangCode":"en","OrigNameLangID":15,"FullOrigName":"Ghent University; 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