Use of circular dichroism and artificial neural networks for the kinetic-spectrophotometric resolution of enantiomers

Sequential injection kinetic spectrophotometric determination of quaternary mixtures of carbamate pesticides in water and fruit samples using artificial neural networks for multivariate calibration

A new analytical method was developed for the simultaneous kinetic spectrophotometric determination of a quaternary carbamate pesticide mixture consisting of carbofuran, propoxur, metolcarb and fenobucarb using sequential injection analysis (SIA). The procedure was based upon the different kinetic properties between the analytes reacted with reagent in flow system in the non-stopped-flow mode, in which their hydrolysis products coupled with diazotized p-nitroaniline in an alkaline medium to form the corresponding colored complexes. The absorbance data from SIA peak time profile were recorded at 510 nm and resolved by the use of back-propagation-artificial neural network (BP-ANN) algorithms for multivariate quantitative analysis. The experimental variables and main network parameters were optimized and each of the pesticides could be determined in the concentration range of 0.5-10.0 microg mL(-1), at a sampling frequency of 18 h(-1). The proposed method was compared to other spectrophotometric methods for simultaneous determination of mixtures of carbamate pesticides, and it was proved to be adequately reliable and was successfully applied to the simultaneous determination of the four pesticide residues in water and fruit samples, obtaining the satisfactory results based on recovery studies (84.7-116.0%).