Evidence map›Paper›PMID 39860751›Full record

ArticleSensors (Basel, Switzerland)2025

Rapid and Simultaneous Detection of Petroleum Hydrocarbons and Organic Pesticides in Soil Based on Electronic Nose.

Cheng Kong, Lin Sun, Xiaodan Li, Yu Yan, Zhiyong Chang, Mo Li, Fuyan Gou, Baojun Rong

Abstract read
In one paragraph

Article in Sensors (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. Article
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

8 authors.

Cheng KongCollege of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China.
Lin SunBeijing Institute of Geohazard Prevention and Control, Beijing 100011, China.
Xiaodan LiChina Northeast Municipal Engineering Design and Research Institute Co., Ltd., Changchun 130021, China.
Yu YanChina Northeast Municipal Engineering Design and Research Institute Co., Ltd., Changchun 130021, China.
Zhiyong ChangCollege of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China.
Mo LiCollege of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China.
Fuyan GouCollege of Geoexploration Science and Technology, Jilin University, Changchun 130022, China.
Baojun RongSchool of Mechanical and Vehicle Engineering, Jilin Engineering Normal University, Changchun 130052, China.

Funding

Jilin Provincial Science & Technology Department 20210203004SFNational Key Research and Development Program of China 2023YFC2812603National Natural Science Foundation of China U22A20184Scientific Research Foundation of the Education Department of Jilin Province JJKH20211075KJScientific Research Foundation of the Education Department of Jilin Province JJKH20220193KJScientific Research Foundation of the Education Department of Jilin Province JJKH20221017KJ
6 · The paper itself

Abstract

The rapid detection of petroleum hydrocarbons and organic pesticides is an important prerequisite for precise soil management. It is also a guarantee for soil quality, environmental safety, and human health. However, the current rapid detection methods are prone to sample matrix interference, complex development processes, short lifespan, and low detection accuracy. Moreover, they face difficulties in achieving simultaneous detection of petroleum hydrocarbons and organic pesticides. In this paper, we developed an electronic nose system for the simultaneous detection of petroleum hydrocarbons and organic pesticides in soil based on gas technology, which includes a sampling module and recognition model. The developed sampling module can simultaneously acquire the odor signals of petroleum hydrocarbons and organic pesticides in soil. The established recognition model can quickly distinguish between healthy soil, soil contaminated by petroleum hydrocarbons, and soil contaminated by organic pesticides. It can also achieve specific recognition of pesticide types and petroleum types. The performance of the developed electronic nose system was verified for real soil, petroleum products, and organic pesticides. The experiment shows that the developed electronic nose system has an accuracy of 100% for three tasks: soil conditions identification, pesticide types identification, and petroleum types identification.

Indexed as

electronic noseorganic pesticide pollutionpetroleum hydrocarbon pollutionrecognition modelsoil rapid detection

Identifiers

PMID39860751
PMCPMC11769389

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LicenceCC BY
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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.