Evidence map›Paper›PMID 42178409›Full record

ReviewAnalytical and bioanalytical chemistry2026

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

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

Abstract readReview
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In one paragraph

Review in Analytical and bioanalytical chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Lijun Gu *Key Laboratory of Food Contact Materials Safety, State Administration for Market Regulation, Jiangsu Product Quality Testing & Inspection Institute, Nanjing, 210007, Jiangsu, China.
Zhenyu Zhao *Faculty of Life Science and Food Engineering, Huaiyin Institute of Technology, Huaian, 223003, China.
Zhaojie ZouFaculty of Life Science and Food Engineering, Huaiyin Institute of Technology, Huaian, 223003, China.
Yuchen GeFaculty of Life Science and Food Engineering, Huaiyin Institute of Technology, Huaian, 223003, China.
Xiao LiuCollege of Biological Engineering, Qingdao University of Science and Technology, Qingdao, 266042, China.
Jinzhu SongKey Laboratory of Food Contact Materials Safety, State Administration for Market Regulation, Jiangsu Product Quality Testing & Inspection Institute, Nanjing, 210007, Jiangsu, China.
Xiangqian LiFaculty of Life Science and Food Engineering, Huaiyin Institute of Technology, Huaian, 223003, China.
Shuai HeFaculty of Life Science and Food Engineering, Huaiyin Institute of Technology, Huaian, 223003, China. heshuai@hyit.edu.cn.
Wei GaoKey Laboratory of Food Contact Materials Safety, State Administration for Market Regulation, Jiangsu Product Quality Testing & Inspection Institute, Nanjing, 210007, Jiangsu, China. jszjgaowei@126.com.
Pei LiuCollege of Biological Engineering, Qingdao University of Science and Technology, Qingdao, 266042, China. liupeiouc@qust.edu.cn.ORCID http://orcid.org/0000-0003-1440-8851

Funding

National Natural Science Foundation of China 32202158Open Project of Key Laboratory of Food Contact Materials Safety, State Administration for Market Regulation WJ202510R10the 2025 National College Students' Innovation and Entrepreneurship Training Program project 202511049027
6 · The paper itself

Abstract

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.

Indexed as

Food AnalysisFood ContaminationMicroplasticsNanoparticlesFood SafetyHumansSpectrum Analysis, RamanMicroplasticsAI-assisted analysisEmerging analytical technologiesFood matrix interferenceMPs/NPs in food

Identifiers

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.