Multiway calibrations based on spectrofluorimetric data derived from kinetic analysis of the hydrolysis reaction of nitrofurans — A comparison of prediction performance

Abstract

A spectrofluorimetric analytical method was researched and developed for the quantitative, simultaneous analysis of nitrofurazone and nitrofurantoin antibiotics. The method was based on the kinetic analysis of their hydrolysis reaction coupled with multivariate calibration methods. These consisted of several different multiway data models, and their prediction performance was compared on the basis of the above reaction. Nitrofurans do not fluoresce but their alkaline hydrolysis products show strong fluorescence at 245nm/456nm (excitation/emission wavelengths) and 240nm/452nm. Different multiway data matrices were acquired at various excitation and/or emission wavelengths, and/or reaction times and resolved by multiway calibration methods, i.e. the parallel factor analysis, unfolded principal component analysis–residual bilinearization and unfolded principal component analysis–residual trilinearization methods. All of these procedures facilitate the second-order advantage. The relationship between the concentration of the analytes and the fluorescence output was found to be nonlinear. Hence, the results from the calibration models were submitted to the radial basis function artificial neural networks for prediction. The best performing prediction model, unfolded principal component analysis–residual bilinearization–radial basis function artificial neural networks, was used to analyze the nitrofurans in fish samples and the results compared well with those obtained from the reference HPLC method.