Evidence map›Paper›PMID 41222346›Full record

ReviewNanomaterials (Basel, Switzerland)2025

Nanomaterial-Enabled Spectroscopic Sensing: Building a New Paradigm for Precision Detection of Pesticide Residues.

Mei Wang, Yue Niu, Hao Peng, Pengcheng Zhang, Quan Bu, Xianghai Song, Shouqi Yuan

Abstract readReview
In one paragraph

Review in Nanomaterials (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Mei WangSchool of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China.ORCID 0000-0002-9390-9816
Yue NiuSchool of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China.
Hao PengSchool of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China.
Pengcheng ZhangSchool of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China.
Quan BuSchool of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China.
Xianghai SongInstitute of the Green Chemistry and Chemical Technology, School of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang 212013, China.
Shouqi YuanResearch Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang 212013, China.

Funding

the National Natural Science Foundation of China, grant number 21905117
6 · The paper itself

Abstract

This review summarizes the application of spectroscopic techniques in pesticide residue analysis, with a focus on the principles, advancements, and challenges of surface-enhanced Raman spectroscopy (SERS), infrared spectroscopy, fluorescence spectroscopy, ultraviolet-visible (UV-Vis) spectroscopy, and hyperspectral imaging (HSI). Nanomaterials, serving as key enhancing substrates, significantly improve the sensitivity and selectivity of these detection methods. This article critically evaluates the strengths and limitations of each technique in practical applications-such as the exceptional sensitivity of SERS versus its dependence on substrate reproducibility, and the non-destructive nature of hyperspectral imaging against the complexity of data processing. Future research directions should emphasize the development of intelligent nanosubstrates, the construction of cross-modal spectral databases, and the miniaturization of integrated spectroscopic-mass spectrometric instruments. These advancements are essential for enhancing the efficiency and reliability of agricultural and food safety monitoring.

Indexed as

hyperspectral imagingnanomaterialspesticide residue detectionSERSspectroscopic techniques

Identifiers

PMID41222346
PMCPMC12608972

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.