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A new modeling strategy for third-order fast high-performance liquid chromatographic data with fluorescence detection. Quantitation of fluoroquinolones in water samples

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Abstract

Matrix augmentation is regularly employed in extended multivariate curve resolution-alternating least-squares (MCR-ALS), as applied to analytical calibration based on second- and third-order data. However, this highly useful concept has almost no correspondence in parallel factor analysis (PARAFAC) of third-order data. In the present work, we propose a strategy to process third-order chromatographic data with matrix fluorescence detection, based on an Augmented PARAFAC model. The latter involves decomposition of a three-way data array augmented along the elution time mode with data for the calibration samples and for each of the test samples. A set of excitation–emission fluorescence matrices, measured at different chromatographic elution times for drinking water samples, containing three fluoroquinolones and uncalibrated interferences, were evaluated using this approach. Augmented PARAFAC exploits the second-order advantage, even in the presence of significant changes in chromatographic profiles from run to run. The obtained relative errors of prediction were ca. 10 % for ofloxacin, ciprofloxacin, and danofloxacin, with a significant enhancement in analytical figures of merit in comparison with previous reports. The results are compared with those furnished by MCR-ALS.

A new modeling strategy for third-order data

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Acknowledgments

The authors are grateful to Universidad Nacional del Litoral (Projects CAI+D 2012 No. 11-11), Universidad Nacional de Rosario, CONICET (Consejo Nacional de Investigaciones Científicas y Técnicas, Project PIP 455), and ANPCyT (Agencia Nacional de Promoción Científica y Tecnológica, Projects PICT 2011-0005 and PICT 2013-0136) for financial support. M.R.A. thanks CONICET for her fellowship.

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Authors and Affiliations

  1. Laboratorio de Desarrollo Analítico y Quimiometría (LADAQ), Cátedra de Química Analítica I, Facultad de Bioquímica y Ciencias Biológicas, Universidad Nacional del Litoral-CONICET, Ciudad Universitaria, 3000, Santa Fe, Argentina

    Mirta R. Alcaráz & Héctor C. Goicoechea

  2. Departamento de Química Analítica, Facultad de Ciencias Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario, Instituto de Química de Rosario (IQUIR-CONICET), Suipacha 531, Rosario, S2002LRK, Argentina

    Santiago A. Bortolato & Alejandro C. Olivieri

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  1. Mirta R. Alcaráz
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  2. Santiago A. Bortolato
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  3. Héctor C. Goicoechea
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  4. Alejandro C. Olivieri
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Correspondence to Héctor C. Goicoechea or Alejandro C. Olivieri.

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Alcaráz, M.R., Bortolato, S.A., Goicoechea, H.C. et al. A new modeling strategy for third-order fast high-performance liquid chromatographic data with fluorescence detection. Quantitation of fluoroquinolones in water samples. Anal Bioanal Chem 407, 1999–2011 (2015). https://doi.org/10.1007/s00216-014-8442-z

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  • DOI: https://doi.org/10.1007/s00216-014-8442-z

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