Literature DB >> 30086953

Multivariate curve resolution strategy for non-quadrilinear type 4 third-order/four way liquid chromatography-excitation-emission fluorescence matrix data.

Maira D Carabajal1, Juan A Arancibia2, Graciela M Escandar3.   

Abstract

For the first time, a third-order/four-way system having instrumental modes depending on each other was experimentally generated and it was successfully resolved. Non-quadrilinear type 4 data, constituted by liquid chromatographic elution times (LC) and excitation-emission fluorescence matrices (EEFMs), were on-line measured using conventional equipment. Thus, third-order/four-way data, valuable for giving rise to highly sensitive and selective methods, were obtained minimizing significantly the experimental work and time, in comparison with the reported strategies for the acquisition of LC-EEFM data. The usefulness of MCR-ALS (multivariate curve resolution-alternating least square) for attaining reliable results from data with two mutually dependent instrumental modes, namely elution time and excitation wavelength modes, was established through the simultaneous quantitation of benz[a]anthracene, chrysene, benzo[b]fluoranthene, and benzo[a]pyrene. Limits of detection in the range 1.0-1.4 ng mL-1 were achieved for the target polycyclic aromatic hydrocarbons, allowing their determination in about 9 min per sample in leaves of different types of tea.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Liquid chromatography-excitation-emission fluorescence; Multivariate curve resolution-alternating least square; Polycyclic aromatic hydrocarbons; Tea samples; Third-order/four-way calibration

Year:  2018        PMID: 30086953     DOI: 10.1016/j.talanta.2018.07.017

Source DB:  PubMed          Journal:  Talanta        ISSN: 0039-9140            Impact factor:   6.057


  1 in total

1.  Flexible Implementation of the Trilinearity Constraint in Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) of Chromatographic and Other Type of Data.

Authors:  Xin Zhang; Romà Tauler
Journal:  Molecules       Date:  2022-04-05       Impact factor: 4.411

  1 in total

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