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Distinguishing Different Varieties of Oolong Tea by Fluorescence Hyperspectral Technology Combined with Chemometrics
Oolong tea is a semi-fermented tea that is popular among people. This study aims to establish a classification method for oolong tea based on fluorescence hyperspectral technology(FHSI) combined with chemometrics. First, the spectral data of Tieguanyin, Benshan, Maoxie and Huangjingui were obtained....
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9368096/ https://www.ncbi.nlm.nih.gov/pubmed/35954110 http://dx.doi.org/10.3390/foods11152344 |
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author | Hu, Yan Wu, Youli Sun, Jie Geng, Jinping Fan, Rongsheng Kang, Zhiliang |
author_facet | Hu, Yan Wu, Youli Sun, Jie Geng, Jinping Fan, Rongsheng Kang, Zhiliang |
author_sort | Hu, Yan |
collection | PubMed |
description | Oolong tea is a semi-fermented tea that is popular among people. This study aims to establish a classification method for oolong tea based on fluorescence hyperspectral technology(FHSI) combined with chemometrics. First, the spectral data of Tieguanyin, Benshan, Maoxie and Huangjingui were obtained. Then, standard normal variation (SNV) and multiple scatter correction (MSC) were used for preprocessing. Principal component analysis (PCA) was used for data visualization, and with tolerance ellipses that were drawn according to Hotelling, outliers in the spectra were removed. Variable importance for the projection (VIP) > 1 in partial least squares discriminant analysis (PLS–DA) was used for feature selection. Finally, the processed spectral data was entered into the support vector machine (SVM) and PLS–DA. MSC_VIP_PLS–DA was the best model for the classification of oolong tea. The results showed that the use of FHSI could accurately distinguish these four types of oolong tea and was able to identify the key wavelengths affecting the tea classification, which were 650.11, 660.29, 665.39, 675.6, 701.17, 706.31, 742.34 and 747.5 nm. In these wavelengths, different kinds of tea have significant differences (p < 0.05). This study could provide a non-destructive and rapid method for future tea identification. |
format | Online Article Text |
id | pubmed-9368096 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93680962022-08-12 Distinguishing Different Varieties of Oolong Tea by Fluorescence Hyperspectral Technology Combined with Chemometrics Hu, Yan Wu, Youli Sun, Jie Geng, Jinping Fan, Rongsheng Kang, Zhiliang Foods Article Oolong tea is a semi-fermented tea that is popular among people. This study aims to establish a classification method for oolong tea based on fluorescence hyperspectral technology(FHSI) combined with chemometrics. First, the spectral data of Tieguanyin, Benshan, Maoxie and Huangjingui were obtained. Then, standard normal variation (SNV) and multiple scatter correction (MSC) were used for preprocessing. Principal component analysis (PCA) was used for data visualization, and with tolerance ellipses that were drawn according to Hotelling, outliers in the spectra were removed. Variable importance for the projection (VIP) > 1 in partial least squares discriminant analysis (PLS–DA) was used for feature selection. Finally, the processed spectral data was entered into the support vector machine (SVM) and PLS–DA. MSC_VIP_PLS–DA was the best model for the classification of oolong tea. The results showed that the use of FHSI could accurately distinguish these four types of oolong tea and was able to identify the key wavelengths affecting the tea classification, which were 650.11, 660.29, 665.39, 675.6, 701.17, 706.31, 742.34 and 747.5 nm. In these wavelengths, different kinds of tea have significant differences (p < 0.05). This study could provide a non-destructive and rapid method for future tea identification. MDPI 2022-08-05 /pmc/articles/PMC9368096/ /pubmed/35954110 http://dx.doi.org/10.3390/foods11152344 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 | Article Hu, Yan Wu, Youli Sun, Jie Geng, Jinping Fan, Rongsheng Kang, Zhiliang Distinguishing Different Varieties of Oolong Tea by Fluorescence Hyperspectral Technology Combined with Chemometrics |
title | Distinguishing Different Varieties of Oolong Tea by Fluorescence Hyperspectral Technology Combined with Chemometrics |
title_full | Distinguishing Different Varieties of Oolong Tea by Fluorescence Hyperspectral Technology Combined with Chemometrics |
title_fullStr | Distinguishing Different Varieties of Oolong Tea by Fluorescence Hyperspectral Technology Combined with Chemometrics |
title_full_unstemmed | Distinguishing Different Varieties of Oolong Tea by Fluorescence Hyperspectral Technology Combined with Chemometrics |
title_short | Distinguishing Different Varieties of Oolong Tea by Fluorescence Hyperspectral Technology Combined with Chemometrics |
title_sort | distinguishing different varieties of oolong tea by fluorescence hyperspectral technology combined with chemometrics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9368096/ https://www.ncbi.nlm.nih.gov/pubmed/35954110 http://dx.doi.org/10.3390/foods11152344 |
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