Evidence map›Paper›PMID 41376081›Full record

ReviewFoods (Basel, Switzerland)2025

Research Progress on the Application of Upconversion Nanoparticles in Heavy Metal Detection in Foodstuff.

Zhiqiang Chen, Kangyao Zhang, Ye He

Abstract readReview
In one paragraph

Review in Foods (Basel, Switzerland), 2025. 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

3 authors.

Zhiqiang ChenSchool of Food Engineering, Zhangzhou Institute of Technology, Zhangzhou 363000, China.
Kangyao ZhangSchool of Advanced Manufacturing, Fuzhou University, Quanzhou 362251, China.
Ye HeCollege of Public Health, Fujian Medical University, Fuzhou 350108, China.

Funding

Education and Science for Young and Middle-aged Teachers of Fujian Provincial Department of Education JAT210859Fujian Provincial Department of Science and Technology 2022J05132the National Natural Science Foundation of China 22304025the Project of Doctoral Research Initiation Fund of 2022 Zhangzhou Institute of Technology ZZYB2202the research project of 2024 Zhangzhou Institute of Technology zzykyk24002
6 · The paper itself

Abstract

Heavy metal contamination in foodstuff poses a serious threat to food safety and human health; therefore, the development of toxic heavy metal detection methods is crucial. However, lots of these methods, based on traditional nanomaterials, have unavoidable limitations, such as high instrument cost, complicated operation procedures, or a long analysis time, which restrict their wide application in heavy metal detection. This review aims to conduct a systematic overview of major analytical methods using novel upconversion nanoparticles (UCNPs) for assessing heavy metal ions in complex food matrices in the context of food safety and show their potential application prospects when combined with big data and artificial intelligence. Due to their unique optical properties, good bio-compatibility, and tunable interfacial chemistry, UCNPs have shown significant detection advantages in the field of food heavy metal analysis. The review summarizes the progress of the application of UCNPs in heavy metal detection in food. Despite the development of new technologies such as artificial intelligence, and the continuous optimization and improvement of its own design, the wide application of UCNPs in food safety detection still has great potential for further development.

Indexed as

detection technologiesfood safetyheavy metalsupconversion nanoparticles (UCNPs)

Identifiers

PMID41376081
PMCPMC12709228

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Registered trials

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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.