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Hazards of using multivariate curve resolution for processing first-order spectral data. A rotational ambiguity
1Departamento de Química Analítica, Facultad de Ciencias Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario, Suipacha 531 (2000), Rosario, Argentina; Instituto de Química Rosario (CONICET-UNR), 27 de Febrero 210 Bis (2000), Rosario, Argentina.
Background:
A growing number of reports are discussing the use of multivariate curve resolution - alternating least-squares (MCR-ALS) to process matrices built with first-order data, e.g., spectra. Although the results are promising, almost no complementary analysis of the impact of rotational ambiguity on the obtained solutions has been reported.
Results:
Several experimental data sets involving spectra (near infrared, UV-visible absorption, fluorescence emission) were processed with MCR-ALS, and then analyzed with channel-wise N-BANDS regarding the presence of rotational ambiguity. In cases of low spectral overlapping, almost unique profiles were found in the retrieved analyte concentration profiles. In cases of high spectral overlapping, however, substantial ambiguity was estimated in the analyte concentration profiles, making the analytical results less reliable. This is even more pronounced when uncalibrated components occur in the test samples. Channel-wise N-BANDS calculations agreed with the results from randomly initialized MCR-ALS models.
Significance:
Researchers using MCR-ALS in multivariate calibration protocols based on first-order data should always accompany the decomposition results with a rotational ambiguity analysis. This would provide insight into the reliability of the retrieved profiles, the estimation of the analyte concentrations and the qualitative interpretation of the spectra.
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