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Article ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 2 ? Original research — experimental, observational, or case-control study. Direct primary evidence. Detection Methods Food & Water Human Health Effects Policy & Risk Sign in to save

Microplastic Contamination and Detection in Food Systems: A Review of Machine Learning, Traditional Methods, and Other Relevant Factors

2025
SURAJIT DAS, Surajit Das, Yemane H. Gebremeskal, Bogdana Vladimirovna Maksimova, Pavel Zuna, Natalya Eremeeva

Summary

This review examines traditional and machine learning approaches to detecting and classifying microplastics in food systems, highlighting the limitations of FTIR, Raman spectroscopy, and SEM in complex food matrices. It identifies AI-assisted methods as promising tools for improving detection accuracy and throughput.

Study Type Environmental

Microplastics (MPs) are widespread contaminants in food, beverages, and drinking water, raising concerns over potential health risks. Accurate and standardized detection a significant analytical chemistry challenge due to complex food matrices and lim

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