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Chemosensors
Special Issues
State-of-the-Art in Electronic Nose Based on Optoelectronic/Electrochemical Sensors
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State-of-the-Art in Electronic Nose Based on Optoelectronic/Electrochemical Sensors

A special issue of Chemosensors (ISSN 2227-9040). This special issue belongs to the section "Applied Chemical Sensors".

Deadline for manuscript submissions: closed (15 November 2021) | Viewed by 11396

Special Issue Editors

Prof. Dr. Jun Wang

E-Mail Website
Guest Editor
College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Rd, Hangzhou 310058, China
Interests: colorimetric sensor; fluorometric sensor; electrochemical sensor; electronic nose
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Zhenbo Wei

E-Mail Website
Guest Editor
Department of Biosystems Engineering, Zhejiang University, Hangzhou 310058, China
Interests: nanocomposites; modified electrode; pattern recognition; intelligent flavor sensing system; food quality detection
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Nowadays, the analysis of volatile organic compounds (VOCs) is very important in various domains. In recent decades, electronic noses based on optical and electrochemical sensor array have emerged as promising alternatives to traditional analytical methods to detect the trace amount of analyte.

The Special Issue of Chemosensors aims to collect both reviews and original research papers on the latest research activities in the field of electronic nose based on optoelectronic/electrochemical sensors, relevant to their applications. Potential topics include, but are not limited to, the following:

  • Novel concepts of electronic nose based on optoelectronic/electrochemical sensors
  • New operating principles for electronic nose based on optoelectronic/electrochemical sensors
  • New sensor substrate and elements for optoelectronic/electrochemical sensors fabrication
  • Digital imaging methods of colorimetric and fluorometric sensors
  • Feature data selection and multivariate data analysis (volatile organic compounds, aqueous analytes, toxic chemicals, etc.)
  • Applications of electronic nose based on optoelectronic/electrochemical sensors

Prof. Dr. Jun Wang
Prof. Dr. Zhenbo Wei
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Chemosensors is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • electronic nose
  • colorimetric sensor
  • fluorometric sensor
  • electrochemical sensor
  • imaging system
  • nanoparticles
  • artificial receptor
  • sensing element
  • system miniaturization
  • statistical analysis and modeling

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Published Papers (3 papers)

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Research

14 pages, 3430 KiB  
Article
Development of Portable E-Nose System for Fast Diagnosis of Whitefly Infestation in Tomato Plant in Greenhouse
by Shaoqing Cui, Lin Cao, Nuris Acosta, Heping Zhu and Peter P. Ling
Chemosensors 2021, 9(11), 297; https://doi.org/10.3390/chemosensors9110297 - 23 Oct 2021
Cited by 13 | Viewed by 3902
Abstract
An electronic nose (E-nose) system equipped with a gas sensor array and real-time control panel was developed for a fast diagnosis of whitefly infestation in tomato plants. Profile changes of volatile organic compounds (VOCs) released from tomato plants under different treatments (i.e., whitefly [...] Read more.
An electronic nose (E-nose) system equipped with a gas sensor array and real-time control panel was developed for a fast diagnosis of whitefly infestation in tomato plants. Profile changes of volatile organic compounds (VOCs) released from tomato plants under different treatments (i.e., whitefly infestation, mechanical damage, and no treatment) were successfully determined by the developed E-nose system. A rapid sensor response with high sensitivity towards whitefly-infested tomato plants was observed in the E-nose system. Results of principal component analysis (PCA) and hierarchical clustering analysis (HCA) indicated that the E-nose system was able to provide accurate distinguishment between whitefly-infested plants and healthy plants, with the first three principal components (PCs) accounting for 87.4% of the classification. To reveal the mechanism of whitefly infestation in tomato plants, VOC profiles of whitefly-infested plants and mechanically damaged plants were investigated by using the E-nose system and GC-MS. VOCs of 2-nonanol, oxime-, methoxy-phenyl, and n-hexadecanoic acid were only detected in whitefly-infested plants, while compounds of dodecane and 4,6-dimethyl were only found in mechanically damaged plant samples. Those unique VOC profiles of different tomato plant groups could be considered as bio-markers for diagnosing different damages. Moreover, the E-nose system was demonstrated to have the capability to differentiate whitefly-infested plants and mechanically damaged plants. The relationship between sensor performance and VOC profiles confirmed that the developed E-nose system could be used as a fast and smart device to detect whitefly infestation in greenhouse cultivation. Full article
(This article belongs to the Special Issue State-of-the-Art in Electronic Nose Based on Optoelectronic/Electrochemical Sensors)
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19 pages, 1870 KiB  
Article
MOS Sensors Array for the Discrimination of Lung Cancer and At-Risk Subjects with Exhaled Breath Analysis
by Davide Marzorati, Luca Mainardi, Giulia Sedda, Roberto Gasparri, Lorenzo Spaggiari and Pietro Cerveri
Chemosensors 2021, 9(8), 209; https://doi.org/10.3390/chemosensors9080209 - 5 Aug 2021
Cited by 25 | Viewed by 3739
Abstract
Lung cancer is characterized by a tremendously high mortality rate and a low 5-year survival rate when diagnosed at a late stage. Early diagnosis of lung cancer drastically reduces its mortality rate and improves survival. Exhaled breath analysis could offer a tool to [...] Read more.
Lung cancer is characterized by a tremendously high mortality rate and a low 5-year survival rate when diagnosed at a late stage. Early diagnosis of lung cancer drastically reduces its mortality rate and improves survival. Exhaled breath analysis could offer a tool to clinicians to improve the ability to detect lung cancer at an early stage, thus leading to a reduction in the associated survival rate. In this paper, we present an electronic nose for the automatic analysis of exhaled breath. A total of five a-specific gas sensors were embedded in the electronic nose, making it sensitive to different volatile organic compounds (VOCs) contained in exhaled breath. Nine features were extracted from each gas sensor response to exhaled breath, identifying the subject breathprint. We tested the electronic nose on a cohort of 80 subjects, equally split between lung cancer and at-risk control subjects. Including gas sensor features and clinical features in a classification model, recall, precision, and accuracy of 78%, 80%, and 77% were reached using a fourfold cross-validation approach. The addition of other a-specific gas sensors, or of sensors specific to certain compounds, could improve the classification accuracy, therefore allowing for the development of a clinical tool to be integrated in the clinical pipeline for exhaled breath analysis and lung cancer early diagnosis. Full article
(This article belongs to the Special Issue State-of-the-Art in Electronic Nose Based on Optoelectronic/Electrochemical Sensors)
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12 pages, 2382 KiB  
Article
The Monitoring of Black-Odor River by Electronic Nose with Chemometrics for pH, COD, TN, and TP
by Shanshan Qiu, Pingzhi Hou, Jingang Huang, Wei Han and Zhiwei Kang
Chemosensors 2021, 9(7), 168; https://doi.org/10.3390/chemosensors9070168 - 5 Jul 2021
Cited by 6 | Viewed by 2673
Abstract
Black-odor rivers are polluted urban rivers that often are black in color and emit a foul odor. They are a severe problem in aquatic systems because they can negatively impact the living conditions of residents and the functioning of ecosystems and local economies. [...] Read more.
Black-odor rivers are polluted urban rivers that often are black in color and emit a foul odor. They are a severe problem in aquatic systems because they can negatively impact the living conditions of residents and the functioning of ecosystems and local economies. Therefore, it is crucial to identify ways to mitigate the water quality parameters that characterize black-odor rivers. In this study, we tested the efficacy of an electronic nose (E-nose), which was inexpensive, fast, and easy to operate, for qualitative recognition analysis and quantitative parameter prediction of samples collected from the Yueliang River in Huzhou City. The E-nose sensors were cross-sensitive to the volatile compounds in black-odor water. The device recognized the samples from different river sites with 100% accuracy based on linear discriminant analysis. For water quality parameter predictions, partial least squares regression models based on E-nose signals were established, and the coefficients between the actual water quality parameters (pH, chemical oxygen demand, total nitrogen content, and total phosphorous content) and the predicted values were very high (R2 > 0.90) both in the training and testing sets. These results indicate that E-nose technology can be a fast, easy-to-build, and cost-effective detection system for black-odor river monitoring. Full article
(This article belongs to the Special Issue State-of-the-Art in Electronic Nose Based on Optoelectronic/Electrochemical Sensors)
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