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Analysis of microplastics in food, mineral water and in mineral water process lines by FTIR and Raman microspectroscopy

Zenodo (CERN European Organization for Nuclear Research) 2024 Score: 35 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.

Kristina Enders, Falk Pollehne, Kristina Enders, Kristina Enders, Kristina Enders, Kristina Enders, Kristina Enders, Kristina Enders, Falk Pollehne, Robin Lenz, Robin Lenz, Robin Lenz, Kristina Enders, Fischer, Dieter, Fischer, Dieter, Robin Lenz, Mareike Schumacher, Robin Lenz, Kristina Enders, Kristina Enders, Kristina Enders, Robin Lenz, Robin Lenz, Kristina Enders, Kristina Enders, Kristina Enders, Robin Lenz, Robin Lenz, Kristina Enders, Kristina Enders, Kristina Enders, Kristina Enders, Kristina Enders, Kristina Enders, Robin Lenz, Kristina Enders, Kristina Enders, Kristina Enders, Kristina Enders, Kristina Enders, Kristina Enders, Kristina Enders, Kristina Enders, Kristina Enders, Robin Lenz, Robin Lenz, Robin Lenz, Robin Lenz, Robin Lenz, Mareike Schumacher, Julia Lötsch, Julia Lötsch, Mareike Schumacher, Kristina Enders, Mareike Schumacher, Mareike Schumacher, Kristina Enders, Julia Lötsch, Julia Lötsch, Julia Lötsch, Julia Lötsch, Julia Lötsch, Julia Lötsch, Gabriele C. Eder, Falk Pollehne, Robin Lenz, Gabriele C. Eder, Martin G.J. Löder Martin G.J. Löder Martin G.J. Löder Martin G.J. Löder Falk Pollehne, Martin G.J. Löder Martin G.J. Löder Fischer, Dieter, Fischer, Dieter, Falk Pollehne, Gabriele C. Eder, Fischer, Dieter, Fischer, Dieter, Martin G.J. Löder Martin G.J. Löder Falk Pollehne, Falk Pollehne, Falk Pollehne, Falk Pollehne, Gabriele C. Eder, Falk Pollehne, Martin G.J. Löder Martin G.J. Löder

Summary

Researchers developed standardised sampling protocols and analytical methods using FTIR and Raman microspectroscopy to detect microplastic particles below 10 µm in beverages, soluble foods, and mineral water production lines. The study traced sources and entry pathways of microplastics into food products and identified preventive measures applicable to industrial processing environments.

Study Type Environmental

The analysis of microplastic particles (MP) is, especially in the range below 10 µm, a complex multi-step process that includes sampling, sample treatment, measurement and data analysis. There is a need for valid methods for the detection of MP in structurally simple foods (beverages, soluble foods, rinsed food surfaces) and along their production processes. We developed such methods with the aim of determining the sources and entry paths of MP and deriving preventive measures. General sampling protocols (SOP) were developed as guidelines for sampling in order to avoid contamination during analysis. For the quantitative analysis of MP, spectroscopic reference databases were generated by measuring packaging materials and producing reference MP particles. Furthermore, SOPs for sample preparation for mineral and drinking water and for water-soluble foods were created to ensure an extensive contamination-free processing. The material analysis was carried out using FTIR and Raman microspectroscopy for the detection of MP in the range from 5 µm to 1 mm. A machine learning software was developed for the evaluation of the sample spectra measured using FTIR, which significantly accelerates this process. The GEPARD software was developed for the Raman evaluation. This presentation focusses, after an introduction in the methods and SOPs which were used, on the results of the analysis of mineral water in disposable and reusable glass and plastic bottles. The bottled end products showed different levels of contamination. In order to identify the sources of the MP contaminations, the entire process line (source water, washing water, filling line, production environment) was sampled. The evaluation along such a production line is shown in the figure. Almost all sources of contamination could be identified. The results show that the presented methods is well suited to determine MP for the analysis of the entry paths of MP in food. Also see: https://micro2024.sciencesconf.org/558972/document

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