Principles and Recent Advances in Electronic Nose and Electronic Tongue for Food Safety and Biomedical Applications

A special issue of Chemosensors (ISSN 2227-9040). This special issue belongs to the section "Electrochemical Devices and Sensors".

Deadline for manuscript submissions: 30 June 2024 | Viewed by 2388

Special Issue Editors


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Guest Editor
Multisensor System and Pattern Recognition Research Group (GISM), Engineering and Architecture Faculty, Universidad de Pamplona, Pamplona 543050, Colombia
Interests: electronic nose; electronic tongue; biomedical applications; pattern recognition methods; machine learning; data acquisition; industrial automation

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Guest Editor
Biosensors and Nanotechnology Group, Faculty of Sciences, Moulay Ismaïl University of Meknes, B.P. 11201 Zitoune, Meknes 50000, Morocco
Interests: breath and urinary volatile organic compounds analysis for diseases monitoring; gas sensor arrays; development of electronic-nose and electronic-tongue technologies; food safety, environmental odour monitoring, and biomedical diagnosis

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Guest Editor
College of Computing and Engineering, Nova Southeastern University, Davie, FL 33314, USA
Interests: electronic noses; electronic tongues; electronic eyes

Special Issue Information

Dear Colleagues,

Food quality generally refers to the evaluation of foods through physical, chemical, or microbiological analysis. It is an aspect of food security that requires innovative methods to keep up with dynamic trends in the complex food chain matrix. On the other hand, it is necessary to explore different emerging technologies that can be used for disease detection and on-line monitoring. These technologies are based on detecting and analyzing chemical compounds in biological samples, such as breath, saliva, sweat, and urine.

The electronic tongue (e-tongue), the electronic nose (e-nose), near-infrared spectroscopy (NIRS), and gas chromatography–mass spectrometry (GC-MS) are advanced analytical approaches with high sensitivity that have been extensively applied in research and industry because of their advantages in rapid quantitative and qualitative food analysis. The e-tongue requires liquid or liquidized samples, but the e-nose, GC-MS, and NIRS offer noninvasive analytical advantages. The potential to measure more diverse food quality factors with these instruments is undoubtedly promising and continues to be unraveled by recent researchers. Keeping pace with developments in this scope is imperative for quality control of unprocessed, processed, and semi-processed foods from farm to fork.

The e-nose has recently been used in biomedical applications for diagnosing and monitoring diseases such as cancer, diabetes, kidney disease, and respiratory diseases. The e-tongue has also been used for the diagnosis and monitoring of diseases such as diabetes, kidney disease, and neurodegenerative diseases. These technologies have the potential to provide rapid, non-invasive, and accurate diagnoses, which could improve disease treatment and management.

This Special Issue invites original research papers and review articles that focus on the recent applications of the e-tongue, the e-nose, NIRS, and GC-MS, either as independent techniques or correlative methods with other analytical instruments and respective chemometrics for food quality and biomedical applications. This is an emerging frontier for increasing breakthroughs and solving challenges directly impacting the food industry and health sector.

Dr. Cristhian Duran
Prof. Dr. Benachir Bouchikhi
Prof. Dr. José A. Ramos
Guest Editors

Manuscript Submission Information

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Keywords

  • electronic nose
  • electronic tongue
  • biomedical applications
  • food industry
  • pattern recognition methods
  • artificial intelligence
  • machine learning
  • data acquisition
  • Internet of Things
  • industrial automation
  • tin oxide-based nanosenors

Published Papers (1 paper)

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Research

31 pages, 9014 KiB  
Article
Prostate Cancer Detection in Colombian Patients through E-Senses Devices in Exhaled Breath and Urine Samples
by Cristhian Manuel Durán Acevedo, Jeniffer Katerine Carrillo Gómez, Carlos Alberto Cuastumal Vasquez and José Ramos
Chemosensors 2024, 12(1), 11; https://doi.org/10.3390/chemosensors12010011 - 5 Jan 2024
Cited by 1 | Viewed by 1876
Abstract
This work consists of a study to detect prostate cancer using E-senses devices based on electronic tongue and electronic nose systems. Therefore, two groups of confirmed prostate cancer and control patients were invited to participate through urine and exhaled breath samples, where the [...] Read more.
This work consists of a study to detect prostate cancer using E-senses devices based on electronic tongue and electronic nose systems. Therefore, two groups of confirmed prostate cancer and control patients were invited to participate through urine and exhaled breath samples, where the control patients group was categorized as Benign Prostatic Hyperplasia, Prostatitis, and Healthy patients. Afterward, the samples were subsequently classified using Pattern Recognition and machine learning methods, where the results were compared through clinical history, obtaining a 92.9% success rate in the PCa and control samples’ classification accuracy by using eTongue and a 100% success rate of classification using eNose. Full article
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