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Zhang YH, Lei PD, Ding Y, Zhai XT, Wan XC, Li WX, Zhang Y, Lv HP, Lin Z, Zhu Y. Uncovering characteristic and enantiomeric distribution of volatile components in Huangshan Maofeng and Zhejiang baked green teas. Food Chem 2025; 465:142001. [PMID: 39581079 DOI: 10.1016/j.foodchem.2024.142001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2024] [Revised: 11/06/2024] [Accepted: 11/09/2024] [Indexed: 11/26/2024]
Abstract
Huangshan Maofeng (HSMF) is a famous baked green tea from the Anhui Province of China, known for its "clean and fresh" flavor. Zhejiang, another major tea-producing province, focuses on the production of green teas. This study aimed to analyze the characteristic aroma components and specific enantiomeric distribution of significant chiral volatile compounds in HSMF and Zhejiang baked green tea (ZJ-BGT) with respect to their origins, cultivars and grades using stir bar sorptive extraction combined with non-targeted gas chromatography-mass spectrometry (GC-MS) and enantiomeric GC-MS approaches. Unique enantiomeric distributions were identified for 2-methylbutanal, γ-nonanolactone, jasmine lactone, α-pinene, cis-linalool oxide (furanoid), and linalool in HSMF and ZJ-BGT. Furthermore, the concentrations of hexanal, cis-3-hexenyl butyrate, geraniol, and the enantiomeric ratio of R-α-terpineol demonstrated a positive correlation with the HSMF grade. Additionally, S-jasmine lactone and R-γ-nonanolactone present in HSMF, along with S-linalool found in ZJ-BGT, significantly contribute to the flavor quality of their respective teas.
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Affiliation(s)
- Yu-Hui Zhang
- Key Laboratory of Tea Quality and Safety Control, Ministry of Agriculture and Rural Affairs, Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou 310008, China; Graduate School of Chinese Academy of Agricultural Sciences, Beijing 100081, China.
| | - Pan-Deng Lei
- Tea Research Institution, Anhui Academy of Agricultural Sciences, Huangshan 245000, China.
| | - Yong Ding
- Tea Research Institution, Anhui Academy of Agricultural Sciences, Huangshan 245000, China.
| | - Xiao-Ting Zhai
- State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei 230036, China.
| | - Xiao-Chun Wan
- State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei 230036, China.
| | - Wei-Xuan Li
- Key Laboratory of Tea Quality and Safety Control, Ministry of Agriculture and Rural Affairs, Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou 310008, China.
| | - Yue Zhang
- Key Laboratory of Tea Quality and Safety Control, Ministry of Agriculture and Rural Affairs, Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou 310008, China.
| | - Hai-Peng Lv
- Key Laboratory of Tea Quality and Safety Control, Ministry of Agriculture and Rural Affairs, Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou 310008, China.
| | - Zhi Lin
- Key Laboratory of Tea Quality and Safety Control, Ministry of Agriculture and Rural Affairs, Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou 310008, China.
| | - Yin Zhu
- Key Laboratory of Tea Quality and Safety Control, Ministry of Agriculture and Rural Affairs, Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou 310008, China.
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Evaluation and Analysis of Elderly Mental Health Based on Artificial Intelligence. Occup Ther Int 2023; 2023:7077568. [PMID: 36817324 PMCID: PMC9935871 DOI: 10.1155/2023/7077568] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 10/04/2022] [Accepted: 10/13/2022] [Indexed: 02/11/2023] Open
Abstract
Objective The purpose is to understand the depression status of the elderly in the community, explore its influencing factors, formulate a comprehensive psychological intervention plan according to the influencing factors, implement demonstration psychological intervention, and evaluate and feedback the effect, so as to provide a reference for improving the mental health of the elderly. Method In order to make the output of different emotional data in LSTM more discriminative, a method to dynamically filter the output of LSTM is proposed. Combining the methods of Attention-LSTM, time-dimensional AI attention, and feature-dimensional AI attention, the best model in this paper is obtained. The multistage stratified cluster sampling method was used to conduct a questionnaire survey on the elderly aged 60 and above in a certain area, including the general demographic characteristics questionnaire of the elderly, the self-rating scale of mental health symptoms, and the health self-management ability of adults. All data were entered into a database using Excel software, and SPSS 19.0 statistical software was used for statistical analysis. Results/Discussion. The detection rate of depression (GDS ≥ 11 points) among the elderly in a community in a certain area was 39.38%. Multivariate logistic regression analysis showed that family history of mental illness, more negative life events, decreased ability of daily living, living alone, and suffering from physical diseases in the past six months were the risk factors for depression in the elderly. Community health education can partially alleviate depression in the elderly. The detection rate and degree of depression of the elderly in the comprehensive psychological intervention group were significantly lower than those in the control group, and the difference was statistically significant (P < 0.05).
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Huangshan Maofeng Green Tea Extracts Prevent Obesity-Associated Metabolic Disorders by Maintaining Homeostasis of Gut Microbiota and Hepatic Lipid Classes in Leptin Receptor Knockout Rats. Foods 2022; 11:foods11192939. [PMID: 36230016 PMCID: PMC9562686 DOI: 10.3390/foods11192939] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 08/30/2022] [Accepted: 09/09/2022] [Indexed: 12/03/2022] Open
Abstract
Huangshan Maofeng green tea (HMGT) is one of the most well-known green teas consumed for a thousand years in China. Research has demonstrated that consumption of green tea effectively improves metabolic disorders. However, the underlying mechanisms of obesity prevention are still not well understood. This study investigated the preventive effect and mechanism of long-term intervention of Huangshan Maofeng green tea water extract (HTE) on obesity-associated metabolic disorders in leptin receptor knockout (Lepr−/−) rats by using gut microbiota and hepatic lipidomics data. The Lepr−/− rats were administered with 700 mg/kg HTE for 24 weeks. Our results showed that HTE supplementation remarkably reduced excessive fat accumulation, as well as ameliorated hyperlipidemia and hepatic steatosis in Lepr−/− rats. In addition, HTE increased gut microbiota diversity and restored the relative abundance of the microbiota responsible for producing short chain fatty acids, including Ruminococcaceae, Faecalibaculum, Veillonellaceae, etc. Hepatic lipidomics analysis found that HTE significantly recovered glycerolipid and glycerophospholipid classes in the liver of Lepr−/− rats. Furthermore, nineteen lipid species, mainly from phosphatidylcholines (PCs), phosphatidylethanolamines (PEs), and triglycerides (TGs), were significantly restored increases, while nine lipid species from TGs and diglycerides (DGs) were remarkably recovered decreases by HTE in the liver of Lepr−/− rats. Our results indicated that prevention of obesity complication by HTE may be possible through maintaining homeostasis of gut microbiota and certain hepatic lipid classes.
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Li M, Luo X, Ho CT, Li D, Guo H, Xie Z. A new strategy for grading of Lu’an guapian green tea by combination of differentiated metabolites and hypoglycaemia effect. Food Res Int 2022; 159:111639. [DOI: 10.1016/j.foodres.2022.111639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 06/30/2022] [Accepted: 07/05/2022] [Indexed: 12/08/2022]
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