Evidence map›Paper›PMID 42197297›Full record

ReviewMolecules (Basel, Switzerland)2026

Electrochemical Sensors for Pesticide Residue Detection.

Jiabin Sun, Xinjian Song, Yuan Zhang

Abstract readReview
In one paragraph

Review in Molecules (Basel, Switzerland), 2026. 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

3 authors.

Jiabin SunHubei Key Laboratory of Biological Resources Protection and Utilization, School of Chemical and Environmental Engineering, Hubei Minzu University, Enshi 445000, China.
Xinjian SongHubei Key Laboratory of Biological Resources Protection and Utilization, School of Chemical and Environmental Engineering, Hubei Minzu University, Enshi 445000, China.
Yuan ZhangCollege of Intelligent Systems Science and Engineering, Hubei Minzu University, Enshi 445000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electrochemical sensors have emerged as promising tools for rapid pesticide screening in food and environmental samples because they combine simple instrumentation, fast response, portability, and compatibility with disposable electrodes. This review organizes recent progress through a cross-system framework linking pesticide class, interfacial electrochemical process, and material design. Carbon materials, metal-organic frameworks and their derivatives, metal nanoparticles, metal compounds, conducting polymers, MXene-based composites, and selected emerging materials are compared in terms of enrichment capability, charge-transfer regulation, catalytic amplification, recognition-layer integration, and suitability for real-sample analysis. Emphasis is placed on issues that are often under-discussed in performance-centered surveys, including matrix interference, electrode fouling, batch-to-batch reproducibility, storage stability, scalability, and cost-effectiveness. Representative examples show that the most useful advances arise not simply from lowering the limit of detection but from improving structure-function understanding and translating interfacial design into robust analytical performance. Future work should prioritize standardized fabrication and benchmarking protocols, in situ and operando identification of active sites and interface evolution, matrix-specific antifouling validation, multiresidue and metabolite analysis, and hybrid portable devices coupled with intelligent readout.

Indexed as

electrochemical sensorsfunctional materialspesticide residue

Identifiers

PMID42197297
PMCPMC13209692

What OpenQuestion 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 OpenQuestion graph.