Net analyte signal-based simultaneous determination of dyes in environmental samples using moving window partial least squares regression with UV-vis spectroscopy

Abstract

The multivariate calibration methods—moving window selection partial least squares regression (MWPLSR) and net analyte signal (NAS)—were employed for simultaneous determination of a mixture of C.I. Disperse Blue 183, C.I. Disperse Blue 79, C.I. Disperse Red 82, C.I. Disperse Red 65, C.I. Disperse Yellow 211 and C.I. Disperse Orange 25 by UV-vis spectrophotometry. The absorption spectra of the six disperse dyes were recorded between 320 and 680 nm. A modified changeable size moving window partial least squares (CSMWPLS) and searching combination moving window partial least squares (SCMWPLS) were proposed to search for an optimized spectral interval and an optimized combination of spectral regions from informative regions obtained by MWPLSR. Different wavelength regions were selected by taking into account different spectral parameters including the starting wavelength, the ending wavelength and wavelength interval. It was found that wavelength selection improved the performance of the corresponding net analyte signal-partial least squares (NAS-PLS) model, in terms of root mean square error (RMSE), compared with the results obtained using whole spectra or direct combination of informative regions for each dye. The importance of calibration design was also investigated by calculating the prediction and validation errors. The influence of using independent validation sets were emphasized. The proposed calibration method gave better results in combination and informative spectral regions for determination of the six disperse dyes without prior separation.