Evidence map›Paper›PMID 42737193›Full record

ArticleFoods (Basel, Switzerland)2026

A Portable Electrochemical Analysis System Integrated with Machine Learning for Rapid Detection of Pungency Intensity in Red and Green Szechuan Peppers (

Di Zhang, Bin Zhang, Shiyu Huang, Xiaobo Zou, Zitao Lin, Kui Zhong, Lei Zhao, Bolin Shi, Lingqin Shen

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2026. 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

9 authors.

Di ZhangKey Laboratory of Food Sensory Analysis, State Administration for Market Regulation, Beijing 100191, China.
Bin ZhangSchool of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China.
Shiyu HuangSchool of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China.
Xiaobo ZouSchool of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China.
Zitao LinJinan Fruit Research Institute, China Federation of Supply and Marketing Co-Operatives, Jinan 250200, China.
Kui ZhongKey Laboratory of Food Sensory Analysis, State Administration for Market Regulation, Beijing 100191, China.ORCID 0000-0001-5341-7086
Lei ZhaoKey Laboratory of Food Sensory Analysis, State Administration for Market Regulation, Beijing 100191, China.
Bolin ShiKey Laboratory of Food Sensory Analysis, State Administration for Market Regulation, Beijing 100191, China.
Lingqin ShenSchool of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang 212013, China.ORCID 0000-0001-8267-2959

Funding

State Administration for Market Regulation 2025SYSKF03001
6 · The paper itself

Abstract

Szechuan pepper pungency is traditionally assessed by subjective sensory panels or laboratory instruments, hindering on-site detection. Perceived numbing sensation does not always correspond directly to alkylamide content because multiple electroactive constituents, including polyphenols and sanshools, may contribute to the overall sensory response. Chromatographic methods quantify individual compounds but may not fully reflect integrated human pungency perception. Electrochemical detection bypasses separation, as the voltammetric response integrates oxidative signals from multiple electroactive species. We developed a portable electrochemical system with a custom programmable-gain potentiostat, three-electrode detector, and STM32-controlled software for differential pulse voltammetry (DPV) measurement. Coupled with machine learning, it assessed Zanthoxylum bungeanum (red peppers) and Zanthoxylum schinifolium (green peppers). Fifteen replicate scans from each of 22 origins yielded 330 DPV curves calibrated against general Labeled Magnitude Scale (gLMS) scores from a trained panel. An artificial neural network (ANN) achieved R

Indexed as

differential pulse voltammetryelectrochemical fingerprintingmachine learningnumbing intensitypungencystandard normal variateSzechuan pepper

Identifiers

PMID42737193
PMCPMC13565175

What OpenQuestion holds

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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.