Development and validation of an efficient HILIC-QQQ-MS/MS method for quantitative and comparative profiling of 45 hydrophilic compounds in four types of tea (Camellia sentences). (1st March 2022)
- Record Type:
- Journal Article
- Title:
- Development and validation of an efficient HILIC-QQQ-MS/MS method for quantitative and comparative profiling of 45 hydrophilic compounds in four types of tea (Camellia sentences). (1st March 2022)
- Main Title:
- Development and validation of an efficient HILIC-QQQ-MS/MS method for quantitative and comparative profiling of 45 hydrophilic compounds in four types of tea (Camellia sentences)
- Authors:
- Wang, Dan
Shi, Lijuan
Fan, Xiaowei
Lou, Huaqiao
Li, Wenting
Li, Yonglin
Ren, Dabing
Yi, Lunzhao - Abstract:
- Graphical abstract: Highlights: An efficient HILIC-QQQ-MS/MS method (8.5 min per run) was developed and validated. Forty-five hydrophilic compounds in tea samples were simultaneously quantified. Amino acids and nucleotides relating to umami had higher content in GT and RAPT. Most alkaloids and nucleosides showed higher contents in fermented tea (BT/RIPT). OPLS-DA model was established to discriminate four types of Yunnan large-leaf tea. Abstract: Hydrophilic constituents are significant for the taste and nutrition of tea, but their simultaneous quantification remains challenging due to the lack of efficient methods. Based on the hydrophilic interaction chromatography coupled with triple quadrupole-tandem mass spectrometry, this work developed and validated an efficient (8.5 min per run), sensitive (LOQ: 0.002–0.493 μg/mL) and accurate method. This method was successfully used to determine the contents of 45 hydrophilic constituents in Yunnan large-leaf tea. Umami amino acids and umami-enhanced nucleotides generally exhibited higher content in green tea and Pu-erh raw tea. By contrast, a few number of amino acids (e.g., proline and γ-aminobutyric acid) and most alkaloids and nucleosides showed significantly higher contents in black tea or Pu-erh ripen tea. By performing the orthogonal partial least squares discriminant analysis, classification models for distinguishing four types of tea, and green tea from Pu-erh raw tea were established.
- Is Part Of:
- Food chemistry. Volume 371(2022)
- Journal:
- Food chemistry
- Issue:
- Volume 371(2022)
- Issue Display:
- Volume 371, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 371
- Issue:
- 2022
- Issue Sort Value:
- 2022-0371-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-03-01
- Subjects:
- Yunnan large-leaf tea -- Hydrophilic constituents -- Quantification -- Hydrophilic interaction chromatography -- Tandem mass spectrometry
Food -- Analysis -- Periodicals
Food -- Composition -- Periodicals
664 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03088146 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.foodchem.2021.131201 ↗
- Languages:
- English
- ISSNs:
- 0308-8146
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3977.284000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 20287.xml