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Chemical Authentication and Speciation of Salvia Botanicals: An Investigation Utilizing GC/Q-ToF and Chemometrics
Members of the genus Salvia are used as culinary herbs and are prized for their purported medicinal attributes. Since physiological effects can vary widely between species of Salvia, it is of great importance to accurately identify botanical material to ensure safety for consumers. In the present st...
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/PMC9322183/ https://www.ncbi.nlm.nih.gov/pubmed/35885375 http://dx.doi.org/10.3390/foods11142132 |
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author | Lee, Joseph Wang, Mei Zhao, Jianping Avula, Bharathi Chittiboyina, Amar G. Li, Jing Wu, Charles Khan, Ikhlas A. |
author_facet | Lee, Joseph Wang, Mei Zhao, Jianping Avula, Bharathi Chittiboyina, Amar G. Li, Jing Wu, Charles Khan, Ikhlas A. |
author_sort | Lee, Joseph |
collection | PubMed |
description | Members of the genus Salvia are used as culinary herbs and are prized for their purported medicinal attributes. Since physiological effects can vary widely between species of Salvia, it is of great importance to accurately identify botanical material to ensure safety for consumers. In the present study, an in-depth chemical investigation is performed utilizing GC/Q-ToF combined with chemometrics. Twenty-four authentic plant samples representing five commonly used Salvia species, viz. S. apiana, S. divinorum, S. mellifera, S. miltiorrhiza, and S. officinalis, are analyzed using a GC/Q-ToF technique. High-resolution spectral data are employed to construct a sample class prediction (SCP) model followed by principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA). This model demonstrates 100% accuracy for both prediction and recognition abilities. Additionally, the marker compounds present in each species are identified. Furthermore, to reduce the time required and increase the confidence level for compound identification and the classification of different Salvia species, a personal compound database and library (PCDL) containing marker and characteristic compounds is constructed. By combining GC/Q-ToF, chemometrics, and PCDL, the unambiguous identification of Salvia botanicals is achieved. This high-throughput method can be utilized for species specificity and to probe the overall quality of various Salvia-based products. |
format | Online Article Text |
id | pubmed-9322183 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93221832022-07-27 Chemical Authentication and Speciation of Salvia Botanicals: An Investigation Utilizing GC/Q-ToF and Chemometrics Lee, Joseph Wang, Mei Zhao, Jianping Avula, Bharathi Chittiboyina, Amar G. Li, Jing Wu, Charles Khan, Ikhlas A. Foods Article Members of the genus Salvia are used as culinary herbs and are prized for their purported medicinal attributes. Since physiological effects can vary widely between species of Salvia, it is of great importance to accurately identify botanical material to ensure safety for consumers. In the present study, an in-depth chemical investigation is performed utilizing GC/Q-ToF combined with chemometrics. Twenty-four authentic plant samples representing five commonly used Salvia species, viz. S. apiana, S. divinorum, S. mellifera, S. miltiorrhiza, and S. officinalis, are analyzed using a GC/Q-ToF technique. High-resolution spectral data are employed to construct a sample class prediction (SCP) model followed by principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA). This model demonstrates 100% accuracy for both prediction and recognition abilities. Additionally, the marker compounds present in each species are identified. Furthermore, to reduce the time required and increase the confidence level for compound identification and the classification of different Salvia species, a personal compound database and library (PCDL) containing marker and characteristic compounds is constructed. By combining GC/Q-ToF, chemometrics, and PCDL, the unambiguous identification of Salvia botanicals is achieved. This high-throughput method can be utilized for species specificity and to probe the overall quality of various Salvia-based products. MDPI 2022-07-19 /pmc/articles/PMC9322183/ /pubmed/35885375 http://dx.doi.org/10.3390/foods11142132 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 Lee, Joseph Wang, Mei Zhao, Jianping Avula, Bharathi Chittiboyina, Amar G. Li, Jing Wu, Charles Khan, Ikhlas A. Chemical Authentication and Speciation of Salvia Botanicals: An Investigation Utilizing GC/Q-ToF and Chemometrics |
title | Chemical Authentication and Speciation of Salvia Botanicals: An Investigation Utilizing GC/Q-ToF and Chemometrics |
title_full | Chemical Authentication and Speciation of Salvia Botanicals: An Investigation Utilizing GC/Q-ToF and Chemometrics |
title_fullStr | Chemical Authentication and Speciation of Salvia Botanicals: An Investigation Utilizing GC/Q-ToF and Chemometrics |
title_full_unstemmed | Chemical Authentication and Speciation of Salvia Botanicals: An Investigation Utilizing GC/Q-ToF and Chemometrics |
title_short | Chemical Authentication and Speciation of Salvia Botanicals: An Investigation Utilizing GC/Q-ToF and Chemometrics |
title_sort | chemical authentication and speciation of salvia botanicals: an investigation utilizing gc/q-tof and chemometrics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9322183/ https://www.ncbi.nlm.nih.gov/pubmed/35885375 http://dx.doi.org/10.3390/foods11142132 |
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