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超高效液相色谱-高分辨质谱联用结合整合过滤策略全面分析茶树花中化学成分
Tea flowers and fresh tea leaves are biological products of tea, but tea flower is often regarded as waste during tea production, resulting in notable waste of tea flower resources. At present, analysis of the chemical components in tea flowers focuses on single types of chemical components such as...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Editorial board of Chinese Journal of Chromatography
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9404204/ https://www.ncbi.nlm.nih.gov/pubmed/35243834 http://dx.doi.org/10.3724/SP.J.1123.2021.07015 |
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author | HUANG, Sichen ZHAO, Hongpeng HU, Yongdan REN, Dabing YI, Lunzhao |
author_facet | HUANG, Sichen ZHAO, Hongpeng HU, Yongdan REN, Dabing YI, Lunzhao |
author_sort | HUANG, Sichen |
collection | PubMed |
description | Tea flowers and fresh tea leaves are biological products of tea, but tea flower is often regarded as waste during tea production, resulting in notable waste of tea flower resources. At present, analysis of the chemical components in tea flowers focuses on single types of chemical components such as amino acids and tea polyphenols, and there are only a few reports on the simultaneous analysis of numerous chemical components in tea flowers. Researchers are not completely clear about the types and amounts of the chemical components in tea flowers; this has hindered the in-depth development and effective utilization of tea flowers. In this study, ultra-performance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS) was used to detect the chemical constituents of tea flowers. This technique was combined with the integrated filtering strategy (IFS) of nitrogen rule filtering (NRF), mass defect filtering (MDF), and diagnostic fragment ion filtering (DFIF) for screening the characteristic mass spectra of the target chemical components. Furthermore, the chemical constituents of tea flowers were annotated with information about the retention time, MS fragmentation, and MS/MS fragmentation. All the qualitative chemical components were divided into six categories with a total of 137 chemical constituents, including 3 alkaloids, 38 flavonoids, 31 phenolic acids and their derivatives, 37 catechins and their derivatives, 18 amino acids, and 10 other components. The internal standard method was used to quantify all the qualitative chemical components. The quantitative results showed that the amounts of the six kinds of chemical components in tea flowers were as follows: amino acids, 9371.42 μg/g; catechins and their derivatives, 9068.43 μg/g; phenolic acids and their derivatives, 8696.92 μg/g; alkaloids, 4392.52 μg/g; flavonoids, 1192.88 μg/g; and others, 139.94 μg/g. Quality control samples were used to evaluate the stability of the instrument and the repeatability of the tested data. Nine representative chemical components with high, medium, and low contents in tea were selected, and the relative standard deviation (RSD) of the results was used to evaluate the repeatability of the data. These nine chemical constituents are selected from amino acids, alkaloids, flavonoids, phenolic acids and their derivatives, catechins and their derivatives, and other components, and the response intensities were different. The relative standard deviations of the nine chemical components were in the range of 2.11% to 12.17%. The above results demonstrated the good stability of the instrument and excellent repeatability of the test data. Chlorogenic acid components (CGAs) and glycosylated quercetin components (GQs) were used as two representative components to explain the entire process of extracting the target compounds by IFS. CGAs comprise a class of special esters formed by the esterification of cinnamic acid derivatives with quinic acid as the parent structure. The most common cinnamic acid derivatives are p-coumaric acid, caffeic acid, and ferulic acid. On the one hand, according to the above information and the different positions and degree of quinic acid esterification, the CGAs were structurally classified as monosubstituted CGAs (Mono-CGAs), disubstituted CGAs (Di-CGAs), and trisubstituted CGAs (Tri-CGAs), and three different mass defect filtering windows were set. Therefore, 751 possible target components were selected from 3537 mass spectra in accordance with the nitrogen rule. On the other hand, 22 target components in accordance with the nitrogen rule were obtained by further screening the m/z 191.0551 ion as the diagnostic fragment ion of the CGAs. Combining the overall analytical data with the above mass defect filtering and diagnostic fragment ion filtering screening results, nine target CGAs were selected and characterized based on the MS information. This study reveals the types and amounts of the chemical components accumulated in tea flowers, thus providing valuable information and serving as data reference for the in-depth development and effective utilization of tea flowers. |
format | Online Article Text |
id | pubmed-9404204 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Editorial board of Chinese Journal of Chromatography |
record_format | MEDLINE/PubMed |
spelling | pubmed-94042042022-09-14 超高效液相色谱-高分辨质谱联用结合整合过滤策略全面分析茶树花中化学成分 HUANG, Sichen ZHAO, Hongpeng HU, Yongdan REN, Dabing YI, Lunzhao Se Pu Articles Tea flowers and fresh tea leaves are biological products of tea, but tea flower is often regarded as waste during tea production, resulting in notable waste of tea flower resources. At present, analysis of the chemical components in tea flowers focuses on single types of chemical components such as amino acids and tea polyphenols, and there are only a few reports on the simultaneous analysis of numerous chemical components in tea flowers. Researchers are not completely clear about the types and amounts of the chemical components in tea flowers; this has hindered the in-depth development and effective utilization of tea flowers. In this study, ultra-performance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS) was used to detect the chemical constituents of tea flowers. This technique was combined with the integrated filtering strategy (IFS) of nitrogen rule filtering (NRF), mass defect filtering (MDF), and diagnostic fragment ion filtering (DFIF) for screening the characteristic mass spectra of the target chemical components. Furthermore, the chemical constituents of tea flowers were annotated with information about the retention time, MS fragmentation, and MS/MS fragmentation. All the qualitative chemical components were divided into six categories with a total of 137 chemical constituents, including 3 alkaloids, 38 flavonoids, 31 phenolic acids and their derivatives, 37 catechins and their derivatives, 18 amino acids, and 10 other components. The internal standard method was used to quantify all the qualitative chemical components. The quantitative results showed that the amounts of the six kinds of chemical components in tea flowers were as follows: amino acids, 9371.42 μg/g; catechins and their derivatives, 9068.43 μg/g; phenolic acids and their derivatives, 8696.92 μg/g; alkaloids, 4392.52 μg/g; flavonoids, 1192.88 μg/g; and others, 139.94 μg/g. Quality control samples were used to evaluate the stability of the instrument and the repeatability of the tested data. Nine representative chemical components with high, medium, and low contents in tea were selected, and the relative standard deviation (RSD) of the results was used to evaluate the repeatability of the data. These nine chemical constituents are selected from amino acids, alkaloids, flavonoids, phenolic acids and their derivatives, catechins and their derivatives, and other components, and the response intensities were different. The relative standard deviations of the nine chemical components were in the range of 2.11% to 12.17%. The above results demonstrated the good stability of the instrument and excellent repeatability of the test data. Chlorogenic acid components (CGAs) and glycosylated quercetin components (GQs) were used as two representative components to explain the entire process of extracting the target compounds by IFS. CGAs comprise a class of special esters formed by the esterification of cinnamic acid derivatives with quinic acid as the parent structure. The most common cinnamic acid derivatives are p-coumaric acid, caffeic acid, and ferulic acid. On the one hand, according to the above information and the different positions and degree of quinic acid esterification, the CGAs were structurally classified as monosubstituted CGAs (Mono-CGAs), disubstituted CGAs (Di-CGAs), and trisubstituted CGAs (Tri-CGAs), and three different mass defect filtering windows were set. Therefore, 751 possible target components were selected from 3537 mass spectra in accordance with the nitrogen rule. On the other hand, 22 target components in accordance with the nitrogen rule were obtained by further screening the m/z 191.0551 ion as the diagnostic fragment ion of the CGAs. Combining the overall analytical data with the above mass defect filtering and diagnostic fragment ion filtering screening results, nine target CGAs were selected and characterized based on the MS information. This study reveals the types and amounts of the chemical components accumulated in tea flowers, thus providing valuable information and serving as data reference for the in-depth development and effective utilization of tea flowers. Editorial board of Chinese Journal of Chromatography 2022-03-08 /pmc/articles/PMC9404204/ /pubmed/35243834 http://dx.doi.org/10.3724/SP.J.1123.2021.07015 Text en https://creativecommons.org/licenses/by/4.0/本文是开放获取文章,遵循CC BY 4.0协议 https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Articles HUANG, Sichen ZHAO, Hongpeng HU, Yongdan REN, Dabing YI, Lunzhao 超高效液相色谱-高分辨质谱联用结合整合过滤策略全面分析茶树花中化学成分 |
title | 超高效液相色谱-高分辨质谱联用结合整合过滤策略全面分析茶树花中化学成分 |
title_full | 超高效液相色谱-高分辨质谱联用结合整合过滤策略全面分析茶树花中化学成分 |
title_fullStr | 超高效液相色谱-高分辨质谱联用结合整合过滤策略全面分析茶树花中化学成分 |
title_full_unstemmed | 超高效液相色谱-高分辨质谱联用结合整合过滤策略全面分析茶树花中化学成分 |
title_short | 超高效液相色谱-高分辨质谱联用结合整合过滤策略全面分析茶树花中化学成分 |
title_sort | 超高效液相色谱-高分辨质谱联用结合整合过滤策略全面分析茶树花中化学成分 |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9404204/ https://www.ncbi.nlm.nih.gov/pubmed/35243834 http://dx.doi.org/10.3724/SP.J.1123.2021.07015 |
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