| Literature DB >> 31260981 |
Jing Zhu1, Fengyuan Zhu1, Luqing Li1, Linlin Cheng1, Liang Zhang1, Yue Sun1, Xiaochun Wan2, Zhengzhu Zhang3.
Abstract
We established a novel Dianhong black tea grades discriminant analytic technique based on a fluorescence image along with carbon quantum dots (CDs) as fluorescent probes. Different grades of Dianhong black tea contain different various amounts of tea polyphenols. Tea polyphenols can quench the fluorescent intensity of CDs, resulting in different fluorescent peaks; Dianhong black tea grades can then be discriminated through the use of principal component analysis and Bayesian analysis. Compared with the additional data processing required in other methods, the advantage of our method is that the fluorescence curve can be used directly, and it achieves satisfactory results. We firstly used CDs combined with chemometrics to identify eight grades of Dianhong black tea, and we also provide a new method that improves the identification rate using nanotechnology to avoid performing complex data processing. Published by Elsevier Ltd.Entities:
Keywords: Bayesian discriminant analysis; Carbamide (PubChem CID: 1176); Carbon quantum dots; Catechins (PubChem CID: 1203); Cobalt Nitrate Hexahydrate (PubChem CID: 24821); Epigallocatechin Gallate (PubChem CID: 65064); Ethanol (PubChem CID: 702); Fluorescence spectroscopic analysis; Grades discriminant; Phenol (PubChem CID: 996); Principal component analysis; Sodium Citrate (PubChem CID: 6224); Theaflavin (PubChem CID: 11980943); Theanine (PubChem CID: 439378); Thiourea (PubChem CID: 2723790)
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Year: 2019 PMID: 31260981 DOI: 10.1016/j.foodchem.2019.125046
Source DB: PubMed Journal: Food Chem ISSN: 0308-8146 Impact factor: 7.514