Modeling nonbilinear total synchronous fluorescence data matrices with a novel adapted partial least squares method

    Authors

    A. V. Schenone; A. D. Gomes; M. J. Culzoni; A. D. Campiglia; M. C. U. de Araujo;H. C. Goicoechea

    Comments

    Authors: contact us about adding a copy of your work at STARS@ucf.edu

    Abbreviated Journal Title

    Anal. Chim. Acta

    Keywords

    Second-order advantage; Synchronous fluorescence; Residual modeling; Ciprofloxacin; POLYCYCLIC AROMATIC-HYDROCARBONS; MULTIVARIATE CALIBRATION; 2ND-ORDER; SPECTROSCOPY; SPECTROMETRY; ALGORITHMS; TUTORIAL; Chemistry, Analytical

    Abstract

    A new residual modeling algorithm for nonbilinear data is presented, namely unfolded partial least squares with interference modeling of non bilinear data by multivariate curve resolution by alternating least squares (U-PLS/IMNB/MCR-ALS). Nonbilinearity represents a challenging data structure problem to achieve analyte quantitation from second-order data in the presence of uncalibrated components. Total synchronous fluorescence spectroscopy (TSFS) generates matrices which constitute a typical example of this kind of data. Although the nonbilinear profile of the interferent can be achieved by modeling TSFS data with unfolded partial least squares with residual bilinearization (U-PLS/RBL), an extremely large number of RBL factors has to be considered. Simulated data show that the new model can conveniently handle the studied analytical problem with better performance than PARAFAC, U-PLS/RBL and MCR-ALS, the latter modeling the unfolded data. Besides, one example involving TSFS real matrices illustrates the ability of the new method to handle experimental data, which consists in the determination of ciprofloxacin in the presence of norfloxacin as interferent in water samples. (C) 2014 Elsevier B.V. All rights reserved.

    Journal Title

    Analytica Chimica Acta

    Volume

    859

    Publication Date

    1-1-2015

    Document Type

    Article

    Language

    English

    First Page

    20

    Last Page

    28

    WOS Identifier

    WOS:000348457300002

    ISSN

    0003-2670

    Share

    COinS