Solvent selection in the quality analysis of white tea by nuclear magnetic resonance spectroscopy
The study aimed to assess the influence of diverse solvent schemes on the qualitative analysis of white tea and to establish a more comprehensive quality evaluation. A systematic study of solvent optimization was carried out using the quality analysis of white tea as an exemplar, highlighting the critical role of selecting appropriate solvents in NMR-based sample preparation process. Six sample dissolution protocols, encompassing extraction and reconstitution solvents, were evaluated. The aqueous methanol solution proved effective as an extraction solvent, offering optimal metabolite coverage and spectral resolution. For reconstitution solvents, D 2 O facilitated identification of specific metabolites, such as amino acids, organic acids and carbohydrates, while DMSO-d 6 exhibited better performance in detecting catechins, alkaloids and lipid resonances. Additionally, DMSO-d 6 enabled better discrimination among various white tea varieties, whereas D 2 O system demonstrated better ability for estimating the storage duration of white tea. The characteristic metabolites were exactly those that each of the two solvents is suited to solubilize. Therefore, it can be concluded that solvents suitable for the detection of a class of metabolites are more likely to highlight differences in that type of metabolites and multi-solvent combination captures more comprehensive information, revealing the necessity of optimizing solvent protocols for different assay targets. • The solubilization of various metabolites in D 2 O and DMSO-d 6 behaves differently. • D 2 O facilitates the identification of amino acids, organic acids and carbohydrates. • DMSO-d 6 exhibits better performance in detecting catechins, alkaloids and lipids. • DMSO-d 6 and D 2 O act better in identifying varieties and storage years, respectively. • Solvents highlight differences in the metabolites that they are suited to solubilize.
Authors
- Jiyang Dong (ORCID: https://orcid.org/0000-0002-1064-6548)
- Biao Huang (ORCID: https://orcid.org/0000-0002-5005-6980)
- Kian‐Kai Cheng (ORCID: https://orcid.org/0000-0002-5894-1781)
- Wei Li
- Yufei Huang (ORCID: https://orcid.org/0000-0001-6268-5357)
- Zijian Wang (ORCID: https://orcid.org/0000-0002-9847-9691)
- Xiaohong Cui (ORCID: https://orcid.org/0000-0002-3201-3952)
- Feifei Lu
- Yang Guo (ORCID: https://orcid.org/0009-0005-6622-8483)
Publication Details
- Journal
- LWT
- Published
- 2024-12-04
- DOI
- https://doi.org/10.1016/j.lwt.2024.117155
- Citations
- 4
- Primary Topic
- Tea Polyphenols and Effects
- Type
- article
- Field-Weighted Citation Impact
- 1.70