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Electronic Sensor Technologies in Monitoring Quality of Tea: A Review

Tea, after water, is the most frequently consumed beverage in the world. The fermentation of tea leaves has a pivotal role in its quality and is usually monitored using the laboratory analytical instruments and olfactory perception of tea tasters. Developing electronic sensing platforms (ESPs), in t...

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Autores principales: Gharibzahedi, Seyed Mohammad Taghi, Barba, Francisco J., Zhou, Jianjun, Wang, Min, Altintas, Zeynep
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9138728/
https://www.ncbi.nlm.nih.gov/pubmed/35624658
http://dx.doi.org/10.3390/bios12050356
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author Gharibzahedi, Seyed Mohammad Taghi
Barba, Francisco J.
Zhou, Jianjun
Wang, Min
Altintas, Zeynep
author_facet Gharibzahedi, Seyed Mohammad Taghi
Barba, Francisco J.
Zhou, Jianjun
Wang, Min
Altintas, Zeynep
author_sort Gharibzahedi, Seyed Mohammad Taghi
collection PubMed
description Tea, after water, is the most frequently consumed beverage in the world. The fermentation of tea leaves has a pivotal role in its quality and is usually monitored using the laboratory analytical instruments and olfactory perception of tea tasters. Developing electronic sensing platforms (ESPs), in terms of an electronic nose (e-nose), electronic tongue (e-tongue), and electronic eye (e-eye) equipped with progressive data processing algorithms, not only can accurately accelerate the consumer-based sensory quality assessment of tea, but also can define new standards for this bioactive product, to meet worldwide market demand. Using the complex data sets from electronic signals integrated with multivariate statistics can, thus, contribute to quality prediction and discrimination. The latest achievements and available solutions, to solve future problems and for easy and accurate real-time analysis of the sensory-chemical properties of tea and its products, are reviewed using bio-mimicking ESPs. These advanced sensing technologies, which measure the aroma, taste, and color profiles and input the data into mathematical classification algorithms, can discriminate different teas based on their price, geographical origins, harvest, fermentation, storage times, quality grades, and adulteration ratio. Although voltammetric and fluorescent sensor arrays are emerging for designing e-tongue systems, potentiometric electrodes are more often employed to monitor the taste profiles of tea. The use of a feature-level fusion strategy can significantly improve the efficiency and accuracy of prediction models, accompanied by the pattern recognition associations between the sensory properties and biochemical profiles of tea.
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spelling pubmed-91387282022-05-28 Electronic Sensor Technologies in Monitoring Quality of Tea: A Review Gharibzahedi, Seyed Mohammad Taghi Barba, Francisco J. Zhou, Jianjun Wang, Min Altintas, Zeynep Biosensors (Basel) Review Tea, after water, is the most frequently consumed beverage in the world. The fermentation of tea leaves has a pivotal role in its quality and is usually monitored using the laboratory analytical instruments and olfactory perception of tea tasters. Developing electronic sensing platforms (ESPs), in terms of an electronic nose (e-nose), electronic tongue (e-tongue), and electronic eye (e-eye) equipped with progressive data processing algorithms, not only can accurately accelerate the consumer-based sensory quality assessment of tea, but also can define new standards for this bioactive product, to meet worldwide market demand. Using the complex data sets from electronic signals integrated with multivariate statistics can, thus, contribute to quality prediction and discrimination. The latest achievements and available solutions, to solve future problems and for easy and accurate real-time analysis of the sensory-chemical properties of tea and its products, are reviewed using bio-mimicking ESPs. These advanced sensing technologies, which measure the aroma, taste, and color profiles and input the data into mathematical classification algorithms, can discriminate different teas based on their price, geographical origins, harvest, fermentation, storage times, quality grades, and adulteration ratio. Although voltammetric and fluorescent sensor arrays are emerging for designing e-tongue systems, potentiometric electrodes are more often employed to monitor the taste profiles of tea. The use of a feature-level fusion strategy can significantly improve the efficiency and accuracy of prediction models, accompanied by the pattern recognition associations between the sensory properties and biochemical profiles of tea. MDPI 2022-05-20 /pmc/articles/PMC9138728/ /pubmed/35624658 http://dx.doi.org/10.3390/bios12050356 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Gharibzahedi, Seyed Mohammad Taghi
Barba, Francisco J.
Zhou, Jianjun
Wang, Min
Altintas, Zeynep
Electronic Sensor Technologies in Monitoring Quality of Tea: A Review
title Electronic Sensor Technologies in Monitoring Quality of Tea: A Review
title_full Electronic Sensor Technologies in Monitoring Quality of Tea: A Review
title_fullStr Electronic Sensor Technologies in Monitoring Quality of Tea: A Review
title_full_unstemmed Electronic Sensor Technologies in Monitoring Quality of Tea: A Review
title_short Electronic Sensor Technologies in Monitoring Quality of Tea: A Review
title_sort electronic sensor technologies in monitoring quality of tea: a review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9138728/
https://www.ncbi.nlm.nih.gov/pubmed/35624658
http://dx.doi.org/10.3390/bios12050356
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