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RGB-statistics derived from Nile red-stained reference plastics for the construction of the PDM (Plastics Detection Model)
Citeerbaar als data publicatie
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 PDM (Plastics Detection Model). Marine Data Archive. https://doi.org/10.14284/512
Contact: Meyers, Nelle

Beschikbaarheid: Creative Commons License Deze dataset valt onder een Creative Commons Naamsvermelding 4.0 Internationaal-licentie.

Beschrijving
Dataset containing RGB-statistics extracted from photographed fluorescent reference particles stained with Nile red. The most abundantly produced plastic polymers worldwide as well as natural materials with high prevalence in the marine environment were considered for this dataset. The spectral data was used to construct a supervised machine learning model that allows to accurately distinguish plastic from natural particles in a cost- and time-efficient way. meer

The dataset was built to train and validate the ‘Plastic Detection Model’ (PDM) in R and contains Red, Green and Blue (RGB) statistics extracted from Nile red-stained reference particles (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 plastic or non-plastic, natural origin of particles, in a cost- and time-efficient way. RGB statistics of the most abundantly produced plastic polymers worldwide as well as natural materials with high prevalence in the marine environment 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 60 plastic and 60 non-plastic particles, where 96 particles (4/5) were randomly selected and used to serve as training data (worksheet tab ‘training data’), while the remaining 24 particles (1/5) were kept as independent validation data (worksheet tab ‘validation data’).

Scope
Thema's:
Milieu-kwaliteit / vervuiling
Kernwoorden:
Marien/Kust, Zoet water, Brak water, Detection method, Fluorescence microscopy, Machine learning, Microplastics, RGB colour data, World

Geografische spreiding

Parameter
RGB (Red, Green, Blue) colour component means and percentiles Methode
RGB (Red, Green, Blue) colour component means and percentiles: Fluorescence microscopy combined with image analysis.

Bijdrage door
Universiteit Gent; Faculteit Bio-ingenieurswetenschappen; Vakgroep Dierwetenschappen en Aquatische Ecologie; Laboratorium voor Aquacultuur en Artemia Reference Center (ARC), meerdata creator
Universiteit Gent; Faculteit Bio-ingenieurswetenschappen; Vakgroep Dierwetenschappen en Aquatische Ecologie; Laboratorium voor Milieutoxicologie (GhEnToxLab), meerdata creator
Vlaams Instituut voor de Zee (VLIZ), meerdata creator
Vlaamse overheid; Beleidsdomein Landbouw en Visserij; Instituut voor landbouw-, visserij en voedingsonderzoek (ILVO), meerdata creator

Gerelateerde datasets
Andere relatie:
RGB-statistics derived from Nile red-stained reference plastics for the construction of the PIM (Polymer Identification Model), meer

Project
ANDROMEDA: Analysis techniques for quantifying nano-and microplastic particles and their degradation in the marine environment, meer

Dataset status: Afgelopen
Data type: Data
Data oorsprong: Onderzoek: labo-experiment
Metadatarecord aangemaakt: 2021-08-23
Informatie laatst gewijzigd: 2021-09-28
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