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A contribution to the harmonization of microplastic analysis in beverages and food

Lebensmittelchemie 2024 1 citation ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 35 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.

Jana Weißer Jana Weißer Jana Weißer Jana Weißer Thomas Hofmann, Jana Weißer Jana Weißer Thomas Hofmann, Thomas Hofmann, Thomas Hofmann, Jana Weißer Thomas Hofmann, Thomas Hofmann, Jana Weißer

Summary

Researchers developed a transparent quality assurance and quality control (QA/QC) framework for hyperspectral microplastic data analysis in beverages and food, using automated evaluation of a ground truth reference image to validate analytical results. The work addresses a significant gap in harmonization efforts where QA/QC for the data analysis step has been largely neglected despite its importance to inter-laboratory comparability.

Abstract Sampling, sample preparation and particle detection are the key steps in microplastics (MP) analysis. In order to harmonize MP analysis, implementing strict measures for quality assurance and control (QA/QC) for all steps is key. However, especially QA and QC for the analysis of hyperspectral MP data has remained widely neglected. To fill this gap, a transparent and detailed QA/QC method for data analysis based on the automated evaluation of a ground truth reference image is presented.

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