Cargando…

Quantitative Analysis and Discrimination of Partially Fermented Teas from Different Origins Using Visible/Near-Infrared Spectroscopy Coupled with Chemometrics

Partially fermented tea such as oolong tea is a popular drink worldwide. Preventing fraud in partially fermented tea has become imperative to protect producers and consumers from possible economic losses. Visible/near-infrared (VIS/NIR) spectroscopy integrated with stepwise multiple linear regressio...

Descripción completa

Detalles Bibliográficos
Autores principales: Wu, Tsung-Hsin, Tung, I-Chun, Hsu, Han-Chun, Kuo, Chih-Chun, Chang, Jenn-How, Chen, Suming, Tsai, Chao-Yin, Chuang, Yung-Kun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7582835/
https://www.ncbi.nlm.nih.gov/pubmed/32977413
http://dx.doi.org/10.3390/s20195451
_version_ 1783599281998921728
author Wu, Tsung-Hsin
Tung, I-Chun
Hsu, Han-Chun
Kuo, Chih-Chun
Chang, Jenn-How
Chen, Suming
Tsai, Chao-Yin
Chuang, Yung-Kun
author_facet Wu, Tsung-Hsin
Tung, I-Chun
Hsu, Han-Chun
Kuo, Chih-Chun
Chang, Jenn-How
Chen, Suming
Tsai, Chao-Yin
Chuang, Yung-Kun
author_sort Wu, Tsung-Hsin
collection PubMed
description Partially fermented tea such as oolong tea is a popular drink worldwide. Preventing fraud in partially fermented tea has become imperative to protect producers and consumers from possible economic losses. Visible/near-infrared (VIS/NIR) spectroscopy integrated with stepwise multiple linear regression (SMLR) and support vector machine (SVM) methods were used for origin discrimination of partially fermented tea from Vietnam, China, and different production areas in Taiwan using the full visible NIR wavelength range (400–2498 nm). The SMLR and SVM models achieved satisfactory results. Models using data from chemical constituents’ specific wavelength ranges exhibited a high correlation with the spectra of teas, and the SMLR analyses improved discrimination of the types and origins when performing SVM analyses. The SVM models’ identification accuracies regarding different production areas in Taiwan were effectively enhanced using a combination of the data within specific wavelength ranges of several constituents. The accuracy rates were 100% for the discrimination of types, origins, and production areas of tea in the calibration and prediction sets using the optimal SVM models integrated with the specific wavelength ranges of the constituents in tea. NIR could be an effective tool for rapid, nondestructive, and accurate inspection of types, origins, and production areas of teas.
format Online
Article
Text
id pubmed-7582835
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-75828352020-10-28 Quantitative Analysis and Discrimination of Partially Fermented Teas from Different Origins Using Visible/Near-Infrared Spectroscopy Coupled with Chemometrics Wu, Tsung-Hsin Tung, I-Chun Hsu, Han-Chun Kuo, Chih-Chun Chang, Jenn-How Chen, Suming Tsai, Chao-Yin Chuang, Yung-Kun Sensors (Basel) Article Partially fermented tea such as oolong tea is a popular drink worldwide. Preventing fraud in partially fermented tea has become imperative to protect producers and consumers from possible economic losses. Visible/near-infrared (VIS/NIR) spectroscopy integrated with stepwise multiple linear regression (SMLR) and support vector machine (SVM) methods were used for origin discrimination of partially fermented tea from Vietnam, China, and different production areas in Taiwan using the full visible NIR wavelength range (400–2498 nm). The SMLR and SVM models achieved satisfactory results. Models using data from chemical constituents’ specific wavelength ranges exhibited a high correlation with the spectra of teas, and the SMLR analyses improved discrimination of the types and origins when performing SVM analyses. The SVM models’ identification accuracies regarding different production areas in Taiwan were effectively enhanced using a combination of the data within specific wavelength ranges of several constituents. The accuracy rates were 100% for the discrimination of types, origins, and production areas of tea in the calibration and prediction sets using the optimal SVM models integrated with the specific wavelength ranges of the constituents in tea. NIR could be an effective tool for rapid, nondestructive, and accurate inspection of types, origins, and production areas of teas. MDPI 2020-09-23 /pmc/articles/PMC7582835/ /pubmed/32977413 http://dx.doi.org/10.3390/s20195451 Text en © 2020 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wu, Tsung-Hsin
Tung, I-Chun
Hsu, Han-Chun
Kuo, Chih-Chun
Chang, Jenn-How
Chen, Suming
Tsai, Chao-Yin
Chuang, Yung-Kun
Quantitative Analysis and Discrimination of Partially Fermented Teas from Different Origins Using Visible/Near-Infrared Spectroscopy Coupled with Chemometrics
title Quantitative Analysis and Discrimination of Partially Fermented Teas from Different Origins Using Visible/Near-Infrared Spectroscopy Coupled with Chemometrics
title_full Quantitative Analysis and Discrimination of Partially Fermented Teas from Different Origins Using Visible/Near-Infrared Spectroscopy Coupled with Chemometrics
title_fullStr Quantitative Analysis and Discrimination of Partially Fermented Teas from Different Origins Using Visible/Near-Infrared Spectroscopy Coupled with Chemometrics
title_full_unstemmed Quantitative Analysis and Discrimination of Partially Fermented Teas from Different Origins Using Visible/Near-Infrared Spectroscopy Coupled with Chemometrics
title_short Quantitative Analysis and Discrimination of Partially Fermented Teas from Different Origins Using Visible/Near-Infrared Spectroscopy Coupled with Chemometrics
title_sort quantitative analysis and discrimination of partially fermented teas from different origins using visible/near-infrared spectroscopy coupled with chemometrics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7582835/
https://www.ncbi.nlm.nih.gov/pubmed/32977413
http://dx.doi.org/10.3390/s20195451
work_keys_str_mv AT wutsunghsin quantitativeanalysisanddiscriminationofpartiallyfermentedteasfromdifferentoriginsusingvisiblenearinfraredspectroscopycoupledwithchemometrics
AT tungichun quantitativeanalysisanddiscriminationofpartiallyfermentedteasfromdifferentoriginsusingvisiblenearinfraredspectroscopycoupledwithchemometrics
AT hsuhanchun quantitativeanalysisanddiscriminationofpartiallyfermentedteasfromdifferentoriginsusingvisiblenearinfraredspectroscopycoupledwithchemometrics
AT kuochihchun quantitativeanalysisanddiscriminationofpartiallyfermentedteasfromdifferentoriginsusingvisiblenearinfraredspectroscopycoupledwithchemometrics
AT changjennhow quantitativeanalysisanddiscriminationofpartiallyfermentedteasfromdifferentoriginsusingvisiblenearinfraredspectroscopycoupledwithchemometrics
AT chensuming quantitativeanalysisanddiscriminationofpartiallyfermentedteasfromdifferentoriginsusingvisiblenearinfraredspectroscopycoupledwithchemometrics
AT tsaichaoyin quantitativeanalysisanddiscriminationofpartiallyfermentedteasfromdifferentoriginsusingvisiblenearinfraredspectroscopycoupledwithchemometrics
AT chuangyungkun quantitativeanalysisanddiscriminationofpartiallyfermentedteasfromdifferentoriginsusingvisiblenearinfraredspectroscopycoupledwithchemometrics