Detection of pesticide in water using two-dimensional fluorescence correlation spectroscopy and N-way partial least squares

To determine the concentration of carbaryl and chlorothalonil in water, the potential of two-dimensional (2D) fluorescence correlation spectra with N-way partial least squares (N-PLS) was investigated. A total of 40 mixture solutions of carbaryl and chlorothalonil were prepared and 27 of them were used to form a calibration set. The excitation-emission matrix (EEM) fluorescence spectra of all samples were measured. Under the excitation perturbation, 2D fluorescence correlation spectra of all samples were calculated and formed a 2D correlation spectral matrix. And N-PLS models for determination of carbaryl and chlorothalonil in water were built based on 2D correlation fluorescence spectral matrix and traditional EEM spectral matrix, respectively. Finally, the performances of N-PLS models using both methods were compared. For chlorothalonil, the root mean square error of calibration (RMSEC) were 3.43 x 10(-6) g L-1 and 5.08 x 10(-6) g L-1, the root mean square errors of prediction (RMSEP) were 5.86 x 10(-6) g L-1 and 8.99 x 10(-6) g L-1 for 2D correlation spectra and EEM spectra, respectively. For carbaryl, the RMSEC were 5.24 x 10(-7) g L-1 and 6.18 x 10(-7), the RMSEP were 9.20 x 10(-7) g L-1 and 9.63 x 10(-7) g L-1 for 2D correlation spectra and EEM spectra, respectively. From the results of this study, it may conclude that 2D fluorescence correlation spectra is superior over the traditional EEM fluorescence spectra in terms of predictability and can be used as an alternative method for detection of organic pollutants in environment. (c) 2020 Elsevier B.V. All rights reserved.