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

• DOI: 10.1007/s00216-014-8442-z
• Publication Date: 2015-01-20T07:35:47Z
• Authors: Mirta R. Alcaráz; Santiago A. Borto...; Héctor C. Goicoechea; Alejandro C. Oliv...
• Keywords: Liquid Chromatography; Augmented Parallel Factor Analysis; 01 natural sciences; 6. Clean water; 0104 chemical sciences; Spectrometry, Fluorescence; Third-Order Data; https://purl.org/becyt/ford/1.4; Water Samples; https://purl.org/becyt/ford/1; Chromatography, High Pressure Liquid; Water Pollutants, Chemical; Fluoroquinolones

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.