Evidence map›Paper›PMID 41312430›Full record

ArticleCurrent research in food science2025

Detection and classification of microplastics in green tea using SERS with gold nanoparticle substrates integrating chemometrics and deep learning.

Rahul Joshi, Samir Adhikari, Donghan Lee, Byoung-Kwan Cho

Abstract read
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In one paragraph

Article in Current research in food science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
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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

4 authors.

Rahul JoshiDepartment of Smart Agricultural Systems Machinery Engineering, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon, 34134, South Korea.
Samir AdhikariBright Quantum Incorporated, 99 Daehak-ro, Yuseong-gu, Daejeon, 34134, South Korea.
Donghan LeeBright Quantum Incorporated, 99 Daehak-ro, Yuseong-gu, Daejeon, 34134, South Korea.
Byoung-Kwan ChoDepartment of Smart Agricultural Systems Machinery Engineering, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon, 34134, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Green tea is consumed worldwide for its health-promoting properties, but it remains vulnerable to microplastic contamination during packaging and processing. Microplastics such as polystyrene (PS) and polyethylene terephthalate (PET) pose potential risks to human health and food safety, underscoring the need for effective detection methods. In this study, Surface-Enhanced Raman Scattering (SERS) using gold nanoparticle substrates was applied to detect and classify PS and PET contamination in four green tea powder varieties across the 400-1650 cm

Indexed as

ChemometricsGreen tea powderMicroplasticsOne dimensional convolutional neural networkPolyethylene terephthalatePolystyreneSurface enhanced Raman scattering

Identifiers

PMID41312430
PMCPMC12650794

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.