0
Systematic Review ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 1 ? Systematic review or meta-analysis. Synthesizes findings across many studies. Strongest evidence. Sign in to save

Hyperspectral imaging: An early systematic review of emerging applications for rapid microplastic analysis

Zenodo (CERN European Organization for Nuclear Research) 2020 1 citation ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 30 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Andrea Faltynkova, Geir Johnsen, Wagner, Martin

Summary

This systematic review examines the emerging use of hyperspectral imaging technology for detecting and analyzing microplastics in environmental samples. Better detection methods matter for human health because accurately measuring microplastic contamination in water, food, and air is essential for understanding our true level of exposure and developing effective strategies to reduce it.

Study Type Review

This document is a protocol for a systematic review on the subject of hyperspectral imaging applied to microplastics analysis.

Sign in to start a discussion.

More Papers Like This

Systematic Review Tier 1

Hyperspectral imaging as an emerging tool to analyze microplastics: A systematic review and recommendations for future development

This systematic review evaluates hyperspectral imaging as a faster, more efficient method for detecting and identifying microplastics. Better detection technology is critical for understanding how much microplastic contamination exists in our food, water, and environment, and for assessing human exposure levels.

Article Tier 2

Detection and identification of microplastics directly in water by hyperspectral imaging

Researchers used hyperspectral imaging to identify different types of microplastics mixed together in water, demonstrating that the technique can distinguish polymer types based on their spectral signatures. This non-destructive, real-time method could improve the speed and accuracy of microplastic monitoring in water samples.

Article Tier 2

Simple and rapid detection of microplastics in seawater using hyperspectral imaging technology

Researchers developed a hyperspectral imaging technique for rapid detection and identification of microplastics in seawater, demonstrating it could analyze multiple particles simultaneously and significantly reduce the time burden compared to traditional individual-particle identification protocols.

Article Tier 2

Spectrometric Detection Of Microplastics In The Environment: A Novel Approach Using Hyperspectral Imaging System

This study developed a novel spectrometric approach to detect microplastics in environmental samples, combining spectral analysis with machine learning classification. The method enabled rapid, accurate identification of multiple polymer types without extensive sample preparation.

Article Tier 2

Hyperspectral Imaging as a Potential Online Detection Method of Microplastics

Researchers evaluated hyperspectral imaging (HSI) as a potential online detection method for microplastics in aquatic environments, assessing its ability to rapidly identify polymer types. The study found HSI shows strong promise for fast polymer identification, though improvements in processing speed are needed for real-time monitoring applications.

Share this paper