Literature DB >> 30015101

Combining excitation-emission matrix fluorescence spectroscopy, parallel factor analysis, cyclodextrin-modified micellar electrokinetic chromatography and partial least squares class-modelling for green tea characterization.

Monica Casale1, Benedetta Pasquini2, Maryam Hooshyari3, Serena Orlandini4, Eleonora Mustorgi3, Cristina Malegori3, Federica Turrini3, Maria Cruz Ortiz5, Luis Antonio Sarabia6, Sandra Furlanetto2.   

Abstract

In this study, an alternative analytical approach for analyzing and characterizing green tea (GT) samples is proposed, based on the combination of excitation-emission matrix (EEM) fluorescence spectroscopy and multivariate chemometric techniques. The three-dimensional spectra of 63 GT samples were recorded using a Perkin-Elmer LS55 luminescence spectrometer; emission spectra were recorded between 295 and 800 nm at excitation wavelength ranging from 200 to 290 nm, with excitation and emission slits both set at 10 nm. The excitation and emission profiles of two factors were obtained using Parallel Factor Analysis (PARAFAC) as a 3-way decomposition method. In this way, for the first time, the spectra of two main fluorophores in green teas have been found. Moreover, a cyclodextrin-modified micellar electrokinetic chromatography method was employed to quantify the most represented catechins and methylxanthines in a subset of 24 GT samples in order to obtain complementary information on the geographical origin of tea. The discrimination ability between the two types of tea has been shown by a Partial Least Squares Class-Modelling performed on the electrokinetic chromatography data, being the sensitivity and specificity of the class model built for the Japanese GT samples 98.70% and 98.68%, respectively. This comprehensive work demonstrates the capability of the combination of EEM fluorescence spectroscopy and PARAFAC model for characterizing, differentiating and analyzing GT samples.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Catechins; Cyclodextrin modified-micellar electrokinetic chromatography; Excitation-emission matrix fluorescence spectroscopy; Green tea; Methylxanthines; Parallel factor analysis

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Year:  2018        PMID: 30015101     DOI: 10.1016/j.jpba.2018.07.001

Source DB:  PubMed          Journal:  J Pharm Biomed Anal        ISSN: 0731-7085            Impact factor:   3.935


  1 in total

1.  Handling Variables, via Inversion of Partial Least Squares Models for Class-Modelling, to Bring Defective Items to Non-Defective Ones.

Authors:  Santiago Ruiz; Luis Antonio Sarabia; María Sagrario Sánchez; María Cruz Ortiz
Journal:  Front Chem       Date:  2021-07-13       Impact factor: 5.221

  1 in total

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