Evidence map›Paper›PMID 34622367›Full record

ReviewMikrochimica acta2021

Rapid field trace detection of pesticide residue in food based on surface-enhanced Raman spectroscopy.

De Zhang, Pei Liang, Wenwen Chen, Zhexiang Tang, Chen Li, Kunyue Xiao, Shangzhong Jin, Dejiang Ni, Zhi Yu

Abstract readReview
PubMed Publisher
In one paragraph

Review in Mikrochimica acta, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.2field-weighted citation impact, top 7% of its field
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

14 citing papers in PubMed, 81 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Current Trends of Raman Spectroscopy in Clinic Settings: Opportunities and Challenges.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Review
  9. Article
  10. Article
  11. Review
  12. Article
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  14. Review
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

9 authors at 3 institutions in 1 country.

De ZhangCollege of Horticulture & Forestry Sciences, Key Laboratory of Horticultural Plant Biology, Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China.
Pei LiangCollege of Optical and Electronic Technology, China Jiliang University, Hangzhou, 310018, China. plianghust@gmail.com.ORCID http://orcid.org/0000-0002-2493-2238
Wenwen ChenCollege of Horticulture & Forestry Sciences, Key Laboratory of Horticultural Plant Biology, Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China.
Zhexiang TangCollege of Optical and Electronic Technology, China Jiliang University, Hangzhou, 310018, China.
Chen LiJiangxi Sericulture and Tea Research Institute, Nanchang, 330203, China.
Kunyue XiaoCollege of Horticulture & Forestry Sciences, Key Laboratory of Horticultural Plant Biology, Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China.
Shangzhong JinCollege of Optical and Electronic Technology, China Jiliang University, Hangzhou, 310018, China.
Dejiang NiCollege of Horticulture & Forestry Sciences, Key Laboratory of Horticultural Plant Biology, Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China.
Zhi YuCollege of Horticulture & Forestry Sciences, Key Laboratory of Horticultural Plant Biology, Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China. yuzhipl@163.com.
Huazhong Agricultural University · CNChina Jiliang University · CNTea Research Institute · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Surface-enhanced Raman spectroscopy is an alternative detection tool for monitoring food security. However, there is still a lack of a conclusion of SERS detection with respect to pesticides and real sample analysis, and the summary of intelligent algorithms in SERS is also a blank. In this review, a comprehensive report of pesticides detection using SERS technology is given. The SERS detection characteristics of different types of pesticides and the influence of substrate on inspection are discussed and compared by the typical ways of classification. The key points, including the progress in real sample analysis and Raman data processing methods with intelligent algorithm, are highlighted. Lastly, major challenges and future research trends of SERS analysis of pesticide residue are also addressed. SERS has been proven to be a powerful technique for rapid test of residue pesticides in complex food matrices, but there still is a tremendous development space for future research.

Indexed as

Food ContaminationPesticide ResiduesSpectrum Analysis, RamanAlgorithmsFood AnalysisMetal NanoparticlesPesticide ResiduesFood residueIntelligent algorithmMicrofluid controlPesticideSERSSERS substrate

Identifiers

PMID34622367
OpenAlexW3203733546

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.