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<p>The ubiquitous presence of microplastics (MPs, &lt; 5&#xa0;mm) and nanoplastics (NPs, &lt; 1&#xa0;μm) in food systems has raised serious concerns regarding food safety and human health. Accurate detection and quantification, however, remain formidable challenges due to the complexity of food matrices, particle heterogeneity, and the lack of harmonized analytical protocols. This review critically examines the emerging analytical technologies that are reshaping the detection landscape of MPs and NPs in food. Emphasis is placed on next-generation methods—including stimulated Raman scattering (SRS) microscopy, surface-enhanced Raman spectroscopy (SERS), hyperspectral imaging (HSI), and microfluidic–nanodroplet platforms—along with artificial intelligence (AI)–assisted analytical frameworks that enable automated identification and classification. The mechanisms by which lipids, proteins, and other food components interfere with nanoscale detection are systematically discussed, highlighting the need for improved pretreatment and matrix-deconvolution strategies. Moreover, we identify persistent gaps in reference materials, quantification standards, and interlaboratory comparability. Looking forward, future progress will depend on the co-development of operational definitions, fit-for-purpose analytical workflows, AI-assisted data interpretation, and reference-material-based interlaboratory validation systems. In this way, methodological innovation can be more effectively translated into reliable food safety assessment and regulatory implementation.</p> Graphical abstract <p></p>

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Emerging analytical technologies for detecting microplastics and nanoplastics in food: bridging challenges and innovations

  • 期刊论文

  • 发表日期：

    2026年5月25日

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  • Lijun Gu,
  • Zhenyu Zhao,
  • Zhaojie Zou,
  • Yuchen Ge,
  • Xiao Liu,
  • Jinzhu Song,
  • Xiangqian Li,
  • Shuai He,
  • Wei Gao,
  • Pei Liu

摘要

The ubiquitous presence of microplastics (MPs, < 5 mm) and nanoplastics (NPs, < 1 μm) in food systems has raised serious concerns regarding food safety and human health. Accurate detection and quantification, however, remain formidable challenges due to the complexity of food matrices, particle heterogeneity, and the lack of harmonized analytical protocols. This review critically examines the emerging analytical technologies that are reshaping the detection landscape of MPs and NPs in food. Emphasis is placed on next-generation methods—including stimulated Raman scattering (SRS) microscopy, surface-enhanced Raman spectroscopy (SERS), hyperspectral imaging (HSI), and microfluidic–nanodroplet platforms—along with artificial intelligence (AI)–assisted analytical frameworks that enable automated identification and classification. The mechanisms by which lipids, proteins, and other food components interfere with nanoscale detection are systematically discussed, highlighting the need for improved pretreatment and matrix-deconvolution strategies. Moreover, we identify persistent gaps in reference materials, quantification standards, and interlaboratory comparability. Looking forward, future progress will depend on the co-development of operational definitions, fit-for-purpose analytical workflows, AI-assisted data interpretation, and reference-material-based interlaboratory validation systems. In this way, methodological innovation can be more effectively translated into reliable food safety assessment and regulatory implementation.

Graphical abstract