125 related articles for article (PubMed ID: 38640534)
1. Dynamic changes of key metabolites in Longjing green tea during processing revealed by widely targeted metabolomic profiling and sensory experiments.
Zeng L; Fu YQ; Gao Y; Wang F; Liang S; Yin JF; Fauconnier ML; Ke L; Xu YQ
Food Chem; 2024 Aug; 450():139373. PubMed ID: 38640534
[TBL] [Abstract][Full Text] [Related]
2. Key umami taste contributors in Longjing green tea uncovered by integrated means of sensory quantitative descriptive analysis, metabolomics, quantification analysis and taste addition experiments.
Shan X; Jiang Y; Zhang S; Chen L; Niu L; Zhang Q; Zhou Q; Wang Y; Yuan H; Li J
Food Chem; 2024 Sep; 453():139628. PubMed ID: 38761731
[TBL] [Abstract][Full Text] [Related]
3. Chemometrics-based investigation of non-volatiles/volatiles flavor of tencha (Camellia sinensis cv. Yabukita, Longjing 43 and Baiye 1).
Yu Q; Huang C; Zhu R; Lu D; Liu L; Lai J; Zhong X; Guan J; Zhou S; Tong Y; Wang Z; Chen P; Guo H; Chu Q; Gong S; Fan F
Food Res Int; 2023 Nov; 173(Pt 2):113461. PubMed ID: 37803791
[TBL] [Abstract][Full Text] [Related]
4. Study on the Dynamic Changes in Non-Volatile Metabolites of Rizhao Green Tea Based on Metabolomics.
Sun A; Liu G; Sun L; Li C; Wu Q; Gao J; Xia Y; Geng Y
Molecules; 2023 Nov; 28(21):. PubMed ID: 37959866
[TBL] [Abstract][Full Text] [Related]
5. Comprehensive investigation on non-volatile and volatile metabolites in four types of green teas obtained from the same tea cultivar of Longjing 43 (Camellia sinensis var. sinensis) using the widely targeted metabolomics.
Shi Y; Zhu Y; Ma W; Shi J; Peng Q; Lin Z; Lv H
Food Chem; 2022 Nov; 394():133501. PubMed ID: 35728471
[TBL] [Abstract][Full Text] [Related]
6. Distinct Changes of Metabolic Profile and Sensory Quality during Qingzhuan Tea Processing Revealed by LC-MS-Based Metabolomics.
Cheng L; Yang Q; Chen Z; Zhang J; Chen Q; Wang Y; Wei X
J Agric Food Chem; 2020 Apr; 68(17):4955-4965. PubMed ID: 32286813
[TBL] [Abstract][Full Text] [Related]
7. Impact of Six Typical Processing Methods on the Chemical Composition of Tea Leaves Using a Single Camellia sinensis Cultivar, Longjing 43.
Wang Y; Kan Z; Thompson HJ; Ling T; Ho CT; Li D; Wan X
J Agric Food Chem; 2019 May; 67(19):5423-5436. PubMed ID: 30403138
[TBL] [Abstract][Full Text] [Related]
8. Differentiating Westlake Longjing tea from the first- and second-grade producing regions using ultra high performance liquid chromatography with quadrupole time-of-flight mass spectrometry-based untargeted metabolomics in combination with chemometrics.
Zhang Q; Zhang YY; Liu Z; Zhang YM; Lu N; Hai GQ; Shao SZ; Zheng QX; Zhang X; Fu HY; Bai CC; Yu YJ; She Y
J Sep Sci; 2020 Jul; 43(14):2794-2803. PubMed ID: 32386337
[TBL] [Abstract][Full Text] [Related]
9. Widely targeted metabolomic analysis reveals dynamic changes in non-volatile and volatile metabolites during green tea processing.
Wang H; Hua J; Yu Q; Li J; Wang J; Deng Y; Yuan H; Jiang Y
Food Chem; 2021 Nov; 363():130131. PubMed ID: 34120048
[TBL] [Abstract][Full Text] [Related]
10. Widely targeted metabolomics using UPLC-QTRAP-MS/MS reveals chemical changes during the processing of black tea from the cultivar Camellia sinensis (L.) O. Kuntze cv. Huangjinya.
Zhou J; Fang T; Li W; Jiang Z; Zhou T; Zhang L; Yu Y
Food Res Int; 2022 Dec; 162(Pt B):112169. PubMed ID: 36461370
[TBL] [Abstract][Full Text] [Related]
11. Non-targeted Metabolomic Analysis Based on Ultra-High-Performance Liquid Chromatography Quadrupole Time-of-Flight Tandem Mass Spectrometry Reveals the Effects of Grafting on Non-volatile Metabolites in Fresh Tea Leaves ( Camellia sinensis L.).
Qi D; Li J; Qiao X; Lu M; Chen W; Miao A; Guo W; Ma C
J Agric Food Chem; 2019 Jun; 67(23):6672-6682. PubMed ID: 31117493
[TBL] [Abstract][Full Text] [Related]
12. Volatile profile analysis and quality prediction of Longjing tea (Camellia sinensis) by HS-SPME/GC-MS.
Lin J; Dai Y; Guo YN; Xu HR; Wang XC
J Zhejiang Univ Sci B; 2012 Dec; 13(12):972-80. PubMed ID: 23225852
[TBL] [Abstract][Full Text] [Related]
13. Metabolomic profiling delineate taste qualities of tea leaf pubescence.
Zhu M; Li N; Zhao M; Yu W; Wu JL
Food Res Int; 2017 Apr; 94():36-44. PubMed ID: 28290365
[TBL] [Abstract][Full Text] [Related]
14. Non-targeted metabolomics analysis reveals dynamic changes of volatile and non-volatile metabolites during oolong tea manufacture.
Chen S; Liu H; Zhao X; Li X; Shan W; Wang X; Wang S; Yu W; Yang Z; Yu X
Food Res Int; 2020 Feb; 128():108778. PubMed ID: 31955752
[TBL] [Abstract][Full Text] [Related]
15. Nontargeted Analysis Using Ultraperformance Liquid Chromatography-Quadrupole Time-of-Flight Mass Spectrometry Uncovers the Effects of Harvest Season on the Metabolites and Taste Quality of Tea (Camellia sinensis L.).
Dai W; Qi D; Yang T; Lv H; Guo L; Zhang Y; Zhu Y; Peng Q; Xie D; Tan J; Lin Z
J Agric Food Chem; 2015 Nov; 63(44):9869-78. PubMed ID: 26494158
[TBL] [Abstract][Full Text] [Related]
16. Analyzing the influence of withering degree on the dynamic changes in non-volatile metabolites and sensory quality of Longjing green tea by non-targeted metabolomics.
Shan X; Yu Q; Chen L; Zhang S; Zhu J; Jiang Y; Yuan H; Zhou Q; Li J; Wang Y; Deng Y; Li J
Front Nutr; 2023; 10():1104926. PubMed ID: 36998915
[TBL] [Abstract][Full Text] [Related]
17. Differential accumulation patterns of flavor compounds in Longjing 43 and Qunti fresh leaves and during processing responding to altitude changes.
Bassiony A; Peng Q; Baldermann S; Feng S; Yang K; Zhang Y; Fu J; Lv H; Lin Z; Shi J
Food Res Int; 2024 Jul; 187():114392. PubMed ID: 38763654
[TBL] [Abstract][Full Text] [Related]
18. Analysis of Young Shoots of 'Anji Baicha' (Camellia sinensis) at Three Developmental Stages Using Nontargeted LC-MS-Based Metabolomics.
Zeng C; Lin H; Liu Z; Liu Z
J Food Sci; 2019 Jul; 84(7):1746-1757. PubMed ID: 31206686
[TBL] [Abstract][Full Text] [Related]
19. Research of Processing Technology of Longjing Tea with 'Baiye 1' Based on Non-Targeted Aroma Metabolomics.
Teng R; Ao C; Huang H; Shi D; Mao Y; Zheng X; Zhao Y
Foods; 2024 Apr; 13(9):. PubMed ID: 38731709
[TBL] [Abstract][Full Text] [Related]
20. Identification of differential volatile and non-volatile compounds in coffee leaves prepared from different tea processing steps using HS-SPME/GC-MS and HPLC-Orbitrap-MS/MS and investigation of the binding mechanism of key phytochemicals with olfactory and taste receptors using molecular docking.
Mei S; Ding J; Chen X
Food Res Int; 2023 Jun; 168():112760. PubMed ID: 37120211
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
