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Papers
20 resultsShowing papers similar to Digital Image Analysis and Multivariate Data Analysis as Tools for the Identification of Microplastics in Surface Waters: The Case of the Vistula River (Central Europe)
ClearIdentification Tools of Microplastics from Surface Water Integrating Digital Image Processing and Statistical Techniques
This study demonstrated that digital image analysis can automate and improve the characterization of microplastic particles collected from river water, capturing detailed shape, color, and size data that manual microscopy cannot easily achieve at scale. Better identification tools like this are essential for standardizing microplastic monitoring across different waterways and research groups.
Identification of Microplastics in Aquatic Environments Using Oxidative Treatment and Automated Image Analysis
Researchers developed a cost-effective and replicable method for detecting microplastics in freshwater environments using oxidative treatment to digest organic matter from water samples, enabling cleaner isolation and more accurate identification of MP particles without requiring expensive instrumentation.
A Machine Learning Approach To Microplastic Detection And Quantification In Aquatic Environments
This study developed a machine learning approach for detecting and quantifying microplastics in aquatic environments, demonstrating that automated image analysis can improve throughput and accuracy compared to manual microscopic counting for environmental monitoring applications.
Analysis of microplastic particles in the Pilica River catchment (Poland) using FTIR imaging microscopy
Researchers analyzed microplastic particles in the Pilica River catchment in Poland, examining sources, distribution, and variability of plastic pollution with a focus on wastewater treatment plants as key emission points. Microplastic concentrations in the river varied spatially and were elevated near wastewater discharge points, confirming WWTPs as significant contributors to river plastic contamination.
Microplastics’ Shape and Morphology Analysis in the Presence of Natural Organic Matter Using Flow Imaging Microscopy
Researchers introduced an innovative flow imaging microscopy approach for rapidly identifying and quantifying microplastics in wastewater treatment plant samples. The study demonstrates that this method can simultaneously capture and classify polyethylene and polystyrene particles while also analyzing how natural organic matter affects microplastic shape and morphology.
Analysis of microplastic particles in the Pilica River catchment (Poland) using FTIR imaging microscopy
Researchers analyzed microplastic distribution across the Pilica River catchment in Poland, assessing contributions from wastewater treatment plants as a key point source. Wastewater treatment plant effluents were identified as a major pathway for microplastic entry into the river system.
Adding depth to microplastics for particle characterization and assessing settling behavior
Researchers developed a method for 3D characterization of microplastic particles to obtain volume and shape data beyond conventional 2D image analysis, improving accuracy in predicting settling behavior and estimating particle mass. Three-dimensional characterization was shown to substantially improve estimates of microplastic transport and sedimentation in water systems.
Detection of Secondary Microplastics in an Aquatic Mesocosm by Means of Object-Based Image Analysis
Researchers evaluated object-based image analysis for detecting secondary microplastics of polypropylene, polyethylene terephthalate, and low-density polyethylene suspended in an aquatic mesocosm under both still and turbulent conditions. The imaging approach successfully identified microplastics in both conditions, supporting its development as a monitoring tool for plastic particles in water.
Deep Learning-Based Image Recognition System for Automated Microplastic Detection and Water Pollution Monitoring
This study developed a deep learning image recognition system to automate the detection and classification of microplastics from microscopy images of water samples. The system achieved high accuracy across particle types and sizes, offering a scalable and less labor-intensive alternative to manual microscopy for large-scale water pollution monitoring.
ImaMPs: Extensive image dataset of microplastics in freshwater from tourist areas in the State of Mexico, Mexico.
Researchers compiled an extensive image dataset of microplastics collected from freshwater bodies in tourist areas of the State of Mexico, providing a visual reference resource to support automated identification and classification of microplastic particles in Mexican aquatic ecosystems.
ImaMPs: Extensive image dataset of microplastics in freshwater from tourist areas in the State of Mexico, Mexico.
Researchers compiled an extensive image dataset of microplastics collected from freshwater bodies in tourist areas of the State of Mexico, providing a visual reference resource to support automated identification and classification of microplastic particles in Mexican aquatic ecosystems.
Multivariate Analysis of Water Quality Measurements on the Danube River
This study applied multivariate statistical analysis to evaluate water quality data collected across multiple depths and cross-sections of the Danube River, identifying patterns in physical, chemical, and biological parameters. Better tools for interpreting complex environmental monitoring data support early detection of pollution including chemical contaminants that interact with microplastics.
Classification and distribution of freshwater microplastics along the Italian Po river by hyperspectral imaging
Researchers used hyperspectral imaging to classify and map the distribution of freshwater microplastics collected from four stations along Italy's Po River, correlating microplastic categories with polymer types and morphological features.
Application of MATLAB and SAS Viya AI models towards the elucidation of potential microplastics in the Neuse River Basin
Researchers applied MATLAB and SAS Viya AI models, including Principal Component Analysis and other machine learning approaches, to identify and characterize microplastics in water samples from the Neuse River Basin, where weathering processes obscure native spectroscopic signatures. The AI-enhanced approach improved microplastic identification accuracy compared to conventional spectroscopic methods alone.
Automatic Counting and Classification of Microplastic Particles
Researchers developed an automatic system for counting and classifying microplastic particles in marine samples, applying image analysis techniques to address the growing problem of plastic debris entering the food chain via marine species ingestion.
Development of a Near-Infrared Imaging System for Identifying Microplastics in Water
Researchers developed a near-infrared imaging system capable of automatically identifying and characterizing microplastics suspended in water, successfully obtaining material identification images without the manual sorting typically required by conventional methods.
Microplastics quantification in sewage sludge: A rapid and cost-effective approach
Researchers developed a rapid and cost-effective image-based method for quantifying microplastics in sewage sludge, using digital image analysis to count and size MP particles without requiring expensive spectroscopic equipment, offering a practical tool for routine sludge monitoring.
Image processing tools in the study of environmental contamination by microplastics: reliability and perspectives
Researchers assessed the reliability of image processing tools for studying microplastic contamination, finding that while these tools offer efficiency gains, inconsistent methodologies limit comparability between studies and call for standardization.
Using optimized particle imaging of micro-Raman to characterize microplastics in water samples
Researchers developed a micro-Raman automatic particle identification technique that can characterize microplastics in water samples up to 100 times faster than traditional point-by-point detection methods, while maintaining high precision for identifying polymer types, sizes, and morphologies.
First evidence of microplastics in surface water of urban waterbodies in Bhopal city, India- abundance and their characteristics
Researchers documented the first evidence of microplastics in surface water of urban waterbodies in Bhopal, India, characterizing particle abundance, morphology, and polymer composition across multiple sites and identifying nearby plastic waste disposal as the primary source.