Evaluation of changes in chemical composition and antioxidant activities from vine tea at different harvest times based on LC-MS, GC-MS, and data fusion algorithms
This study systematically analyzed the chemical composition of vine tea using LC-MS and GC–MS to determine its optimal harvest time and key antioxidant compounds. By employing mass defect filtering (MDF) and a data fusion algorithm, the study examined compositional changes across different harvestin...
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| Published in | Food Chemistry: X Vol. 27; p. 102363 |
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| Main Authors | , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Netherlands
Elsevier Ltd
01.04.2025
Elsevier |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2590-1575 2590-1575 |
| DOI | 10.1016/j.fochx.2025.102363 |
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| Abstract | This study systematically analyzed the chemical composition of vine tea using LC-MS and GC–MS to determine its optimal harvest time and key antioxidant compounds. By employing mass defect filtering (MDF) and a data fusion algorithm, the study examined compositional changes across different harvesting periods. The results identified 62 and 57 compounds through GC–MS and LC-MS, respectively. In vitro antioxidant assays revealed that vine tea harvested in July exhibited the strongest antioxidant activity. Correlation analysis further identified five key antioxidant compounds: myricetin, dihydromyricetin, quercetin, kaempferol, and quercitrin. This research not only clarifies the primary substances responsible for vine tea's antioxidant properties but also provides scientific guidance for optimizing harvest timing. Furthermore, the integrated analytical approach adopted in this study offers a novel strategy for exploring the chemical composition and bioactivity of vine tea and other traditional Chinese herbal medicines, paving the way for further advancements in this field.
•GC-MS and LC-MS identified 62 volatile and 57 non-volatile compounds.•Machine learning algorithms and data fusion strategies screened 24 chemical components across different vine tea periods.•The vine tea harvested in late July exhibited the strongest antioxidant activity.•Myricetin, dihydromyricetin, quercetin, kaempferol and quercitrin were confirmed as vine tea's antioxidant components. |
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| AbstractList | This study systematically analyzed the chemical composition of vine tea using LC-MS and GC-MS to determine its optimal harvest time and key antioxidant compounds. By employing mass defect filtering (MDF) and a data fusion algorithm, the study examined compositional changes across different harvesting periods. The results identified 62 and 57 compounds through GC-MS and LC-MS, respectively.
antioxidant assays revealed that vine tea harvested in July exhibited the strongest antioxidant activity. Correlation analysis further identified five key antioxidant compounds: myricetin, dihydromyricetin, quercetin, kaempferol, and quercitrin. This research not only clarifies the primary substances responsible for vine tea's antioxidant properties but also provides scientific guidance for optimizing harvest timing. Furthermore, the integrated analytical approach adopted in this study offers a novel strategy for exploring the chemical composition and bioactivity of vine tea and other traditional Chinese herbal medicines, paving the way for further advancements in this field. This study systematically analyzed the chemical composition of vine tea using LC-MS and GC–MS to determine its optimal harvest time and key antioxidant compounds. By employing mass defect filtering (MDF) and a data fusion algorithm, the study examined compositional changes across different harvesting periods. The results identified 62 and 57 compounds through GC–MS and LC-MS, respectively. In vitro antioxidant assays revealed that vine tea harvested in July exhibited the strongest antioxidant activity. Correlation analysis further identified five key antioxidant compounds: myricetin, dihydromyricetin, quercetin, kaempferol, and quercitrin. This research not only clarifies the primary substances responsible for vine tea's antioxidant properties but also provides scientific guidance for optimizing harvest timing. Furthermore, the integrated analytical approach adopted in this study offers a novel strategy for exploring the chemical composition and bioactivity of vine tea and other traditional Chinese herbal medicines, paving the way for further advancements in this field. •GC-MS and LC-MS identified 62 volatile and 57 non-volatile compounds.•Machine learning algorithms and data fusion strategies screened 24 chemical components across different vine tea periods.•The vine tea harvested in late July exhibited the strongest antioxidant activity.•Myricetin, dihydromyricetin, quercetin, kaempferol and quercitrin were confirmed as vine tea's antioxidant components. This study systematically analyzed the chemical composition of vine tea using LC-MS and GC-MS to determine its optimal harvest time and key antioxidant compounds. By employing mass defect filtering (MDF) and a data fusion algorithm, the study examined compositional changes across different harvesting periods. The results identified 62 and 57 compounds through GC-MS and LC-MS, respectively. In vitro antioxidant assays revealed that vine tea harvested in July exhibited the strongest antioxidant activity. Correlation analysis further identified five key antioxidant compounds: myricetin, dihydromyricetin, quercetin, kaempferol, and quercitrin. This research not only clarifies the primary substances responsible for vine tea's antioxidant properties but also provides scientific guidance for optimizing harvest timing. Furthermore, the integrated analytical approach adopted in this study offers a novel strategy for exploring the chemical composition and bioactivity of vine tea and other traditional Chinese herbal medicines, paving the way for further advancements in this field.This study systematically analyzed the chemical composition of vine tea using LC-MS and GC-MS to determine its optimal harvest time and key antioxidant compounds. By employing mass defect filtering (MDF) and a data fusion algorithm, the study examined compositional changes across different harvesting periods. The results identified 62 and 57 compounds through GC-MS and LC-MS, respectively. In vitro antioxidant assays revealed that vine tea harvested in July exhibited the strongest antioxidant activity. Correlation analysis further identified five key antioxidant compounds: myricetin, dihydromyricetin, quercetin, kaempferol, and quercitrin. This research not only clarifies the primary substances responsible for vine tea's antioxidant properties but also provides scientific guidance for optimizing harvest timing. Furthermore, the integrated analytical approach adopted in this study offers a novel strategy for exploring the chemical composition and bioactivity of vine tea and other traditional Chinese herbal medicines, paving the way for further advancements in this field. This study systematically analyzed the chemical composition of vine tea using LC-MS and GC–MS to determine its optimal harvest time and key antioxidant compounds. By employing mass defect filtering (MDF) and a data fusion algorithm, the study examined compositional changes across different harvesting periods. The results identified 62 and 57 compounds through GC–MS and LC-MS, respectively. In vitro antioxidant assays revealed that vine tea harvested in July exhibited the strongest antioxidant activity. Correlation analysis further identified five key antioxidant compounds: myricetin, dihydromyricetin, quercetin, kaempferol, and quercitrin. This research not only clarifies the primary substances responsible for vine tea's antioxidant properties but also provides scientific guidance for optimizing harvest timing. Furthermore, the integrated analytical approach adopted in this study offers a novel strategy for exploring the chemical composition and bioactivity of vine tea and other traditional Chinese herbal medicines, paving the way for further advancements in this field. This study systematically analyzed the chemical composition of vine tea using LC-MS and GC–MS to determine its optimal harvest time and key antioxidant compounds. By employing mass defect filtering (MDF) and a data fusion algorithm, the study examined compositional changes across different harvesting periods. The results identified 62 and 57 compounds through GC–MS and LC-MS, respectively. In vitro antioxidant assays revealed that vine tea harvested in July exhibited the strongest antioxidant activity. Correlation analysis further identified five key antioxidant compounds: myricetin, dihydromyricetin, quercetin, kaempferol, and quercitrin. This research not only clarifies the primary substances responsible for vine tea's antioxidant properties but also provides scientific guidance for optimizing harvest timing. Furthermore, the integrated analytical approach adopted in this study offers a novel strategy for exploring the chemical composition and bioactivity of vine tea and other traditional Chinese herbal medicines, paving the way for further advancements in this field. •GC-MS and LC-MS identified 62 volatile and 57 non-volatile compounds.•Machine learning algorithms and data fusion strategies screened 24 chemical components across different vine tea periods.•The vine tea harvested in late July exhibited the strongest antioxidant activity.•Myricetin, dihydromyricetin, quercetin, kaempferol and quercitrin were confirmed as vine tea's antioxidant components. |
| ArticleNumber | 102363 |
| Author | Ocholi, Simon Sani Zhang, Zhonglian Hou, Yu Zhao Fu, Zhifei Zhang, Lele Zhang, Zixin Liu, Changjun Wang, Liming Han, Lifeng |
| Author_xml | – sequence: 1 givenname: Lele surname: Zhang fullname: Zhang, Lele organization: State Key Laboratory of Component-Based Chinese Medicine, Tianjin Key Laboratory of TCM Chemistry and Analysis, Haihe Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai District, Tianjin 301617, China – sequence: 2 givenname: Zixin surname: Zhang fullname: Zhang, Zixin organization: State Key Laboratory of Component-Based Chinese Medicine, Tianjin Key Laboratory of TCM Chemistry and Analysis, Haihe Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai District, Tianjin 301617, China – sequence: 3 givenname: Yu Zhao surname: Hou fullname: Hou, Yu Zhao organization: State Key Laboratory of Component-Based Chinese Medicine, Tianjin Key Laboratory of TCM Chemistry and Analysis, Haihe Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai District, Tianjin 301617, China – sequence: 4 givenname: Simon Sani surname: Ocholi fullname: Ocholi, Simon Sani organization: State Key Laboratory of Component-Based Chinese Medicine, Tianjin Key Laboratory of TCM Chemistry and Analysis, Haihe Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai District, Tianjin 301617, China – sequence: 5 givenname: Liming surname: Wang fullname: Wang, Liming organization: State Key Laboratory of Component-Based Chinese Medicine, Tianjin Key Laboratory of TCM Chemistry and Analysis, Haihe Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai District, Tianjin 301617, China – sequence: 6 givenname: Zhifei surname: Fu fullname: Fu, Zhifei organization: State Key Laboratory of Component-Based Chinese Medicine, Tianjin Key Laboratory of TCM Chemistry and Analysis, Haihe Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai District, Tianjin 301617, China – sequence: 7 givenname: Changjun surname: Liu fullname: Liu, Changjun organization: Guangzhou YIDA Biotechnology Co., Ltd, China – sequence: 8 givenname: Zhonglian surname: Zhang fullname: Zhang, Zhonglian email: zzl0605@163.com organization: Yunnan Key Laboratory of Southern Medicine Utilization, Yunnan Branch of Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences, Peking Union Medical College, Jinghong 666100, China – sequence: 9 givenname: Lifeng surname: Han fullname: Han, Lifeng email: hanlifeng@tjutcm.edu.cn organization: State Key Laboratory of Component-Based Chinese Medicine, Tianjin Key Laboratory of TCM Chemistry and Analysis, Haihe Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai District, Tianjin 301617, China |
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| Keywords | Mass defect filtering Vine tea Machine learning algorithm data fusion Antioxidant |
| Language | English |
| License | This is an open access article under the CC BY-NC-ND license. 2025 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
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| Title | Evaluation of changes in chemical composition and antioxidant activities from vine tea at different harvest times based on LC-MS, GC-MS, and data fusion algorithms |
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