On the performance of multiway methods for simultaneous quantification of two fluoroquinolones in urine samples by fluorescence spectroscopy and second-order calibration strategies

• Multiway methods were compared for analysis of MOX and CIP in urine using EEM data.
• Performance of the methods depends on the EEM subset and the calibration strategy.
• UPLS/RBL allows for the successful determination of both analytes in all conditions.

In the present work, the analytical performance of three multi-way algorithms has been evaluated. The proposed analytical problem was the simultaneous determination of moxifloxacin and ciprofloxacin in human urine samples using fluorescence spectroscopy. Parallel factor analysis (PARAFAC), self-weighted alternating trilinear decomposition (SWATLD) and unfolded partial least squares combined with the residual bilinearization procedure (U-PLS/RBL) have been compared, regarding their ability to solve the proposed problem. In this study, “second-order advantage” was also exploited for the mentioned algorithms through different calibration strategies. The three-way data was obtained via fluorescence spectroscopy, so that excitation–emission matrices (EEM) of the samples were recorded as the analytical signals. The accuracy and precision of each individual algorithm for analyzing the drugs in urine samples were compared using root mean square error of prediction (RMSEP), recovery and elliptical joint confidence region (EJCR) plots. The results revealed that each of the three algorithms could be applied for determination of moxifloxacin and ciprofloxacin, despite different EEM subsets and calibration strategies. However, better analytical performances were observed through PARAFAC and U-PLS/RBL modeling for MOX and CIP, respectively. So, by coupling the multi-way decomposition algorithms with fluorescence spectroscopy, a main part of preliminary sample preparation steps can be eliminated and experimental procedure might be significantly simplified, while achieving desirable analytical performance.

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