A Systematic Review of the Use of Electronic Nose and Tongue Technologies for Detecting Food Contaminants
Sensor operations in the food industry are faced with several major challenges, including in sensitivity, selectivity, accuracy and rapid detection. Among emerging technologies, e-nose and e-tongue systems have attracted much attention from researchers. This review examines 112 studies published fro...
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MDPI AG
2025-07-01
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| Series: | Chemosensors |
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| Online Access: | https://www.mdpi.com/2227-9040/13/7/262 |
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| author | Muhammad Zia Ul Haq Baljit Singh Xolile Fuku Ahmed Barhoum Furong Tian |
| author_facet | Muhammad Zia Ul Haq Baljit Singh Xolile Fuku Ahmed Barhoum Furong Tian |
| author_sort | Muhammad Zia Ul Haq |
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| description | Sensor operations in the food industry are faced with several major challenges, including in sensitivity, selectivity, accuracy and rapid detection. Among emerging technologies, e-nose and e-tongue systems have attracted much attention from researchers. This review examines 112 studies published from 2004 to 2025, and examines the functionalities and performance in detecting various food product-associated analytes. The sensitivity of e-nose and e-tongue systems was analyzed using various data processing techniques. Recent research and development in leading countries (i.e., China, United Kingdom, Columbia, India, Portugal, Spain, Hungary, Ireland) was examined. The findings indicate that principal component analysis (PCA) was the most widely used technique, while more articles were published in 2021. Worldwide research contributions showed China at the forefront of e-nose studies (26.7%) and Spain leading in e-tongue research (30%). The highest sensitivity values were 99.0% for the e-nose in 2015 and 100% for the e-tongue in 2012. In specific applications, the e-nose achieved a maximum average sensitivity of 15% in apple analysis, while the e-tongue achieved a maximum average sensitivity of 40.5% in water samples. Furthermore, the review presents an in-depth discussion of key parameters, including food sample types, citation rates, analysis techniques, accuracy, and sensitivity, with graphical representations for enhanced clarity. |
| format | Article |
| id | doaj-art-2b6443e4ff5f4a5889b1c3533cbb4324 |
| institution | Matheson Library |
| issn | 2227-9040 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
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| series | Chemosensors |
| spelling | doaj-art-2b6443e4ff5f4a5889b1c3533cbb43242025-07-25T13:18:06ZengMDPI AGChemosensors2227-90402025-07-0113726210.3390/chemosensors13070262A Systematic Review of the Use of Electronic Nose and Tongue Technologies for Detecting Food ContaminantsMuhammad Zia Ul Haq0Baljit Singh1Xolile Fuku2Ahmed Barhoum3Furong Tian4Nanolab Research Centre, Physical to Life Sciences Research Hub, Technological University Dublin, Camden Row, D08 CKP1 Dublin, IrelandNanolab Research Centre, Physical to Life Sciences Research Hub, Technological University Dublin, Camden Row, D08 CKP1 Dublin, IrelandInstitute of Nanotechnology and Water Sustainability, College of Science, Engineering and Technology, University of South Africa, Florida Science Campus, Johannesburg 1710, South AfricaNanolab Research Centre, Physical to Life Sciences Research Hub, Technological University Dublin, Camden Row, D08 CKP1 Dublin, IrelandNanolab Research Centre, Physical to Life Sciences Research Hub, Technological University Dublin, Camden Row, D08 CKP1 Dublin, IrelandSensor operations in the food industry are faced with several major challenges, including in sensitivity, selectivity, accuracy and rapid detection. Among emerging technologies, e-nose and e-tongue systems have attracted much attention from researchers. This review examines 112 studies published from 2004 to 2025, and examines the functionalities and performance in detecting various food product-associated analytes. The sensitivity of e-nose and e-tongue systems was analyzed using various data processing techniques. Recent research and development in leading countries (i.e., China, United Kingdom, Columbia, India, Portugal, Spain, Hungary, Ireland) was examined. The findings indicate that principal component analysis (PCA) was the most widely used technique, while more articles were published in 2021. Worldwide research contributions showed China at the forefront of e-nose studies (26.7%) and Spain leading in e-tongue research (30%). The highest sensitivity values were 99.0% for the e-nose in 2015 and 100% for the e-tongue in 2012. In specific applications, the e-nose achieved a maximum average sensitivity of 15% in apple analysis, while the e-tongue achieved a maximum average sensitivity of 40.5% in water samples. Furthermore, the review presents an in-depth discussion of key parameters, including food sample types, citation rates, analysis techniques, accuracy, and sensitivity, with graphical representations for enhanced clarity.https://www.mdpi.com/2227-9040/13/7/262food safetye-nosee-tongueanalytical methodsdata processing techniqueselectrochemical sensor |
| spellingShingle | Muhammad Zia Ul Haq Baljit Singh Xolile Fuku Ahmed Barhoum Furong Tian A Systematic Review of the Use of Electronic Nose and Tongue Technologies for Detecting Food Contaminants Chemosensors food safety e-nose e-tongue analytical methods data processing techniques electrochemical sensor |
| title | A Systematic Review of the Use of Electronic Nose and Tongue Technologies for Detecting Food Contaminants |
| title_full | A Systematic Review of the Use of Electronic Nose and Tongue Technologies for Detecting Food Contaminants |
| title_fullStr | A Systematic Review of the Use of Electronic Nose and Tongue Technologies for Detecting Food Contaminants |
| title_full_unstemmed | A Systematic Review of the Use of Electronic Nose and Tongue Technologies for Detecting Food Contaminants |
| title_short | A Systematic Review of the Use of Electronic Nose and Tongue Technologies for Detecting Food Contaminants |
| title_sort | systematic review of the use of electronic nose and tongue technologies for detecting food contaminants |
| topic | food safety e-nose e-tongue analytical methods data processing techniques electrochemical sensor |
| url | https://www.mdpi.com/2227-9040/13/7/262 |
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