Research Info

Title
Application of Response Surface Methodology and Genetic Algorithm for Optimization and Determination of Iron in Food Samples by Dispersive Liquid–Liquid Microextraction
Type Article
Keywords
Application of Response Surface Methodology and Genetic Algorithm for Optimization and Determination of Iron in Food Samples by Dispersive Liquid–Liquid Microextraction
Abstract
A simple and facile method was developed for the determination of trace amount of iron. The method is based on the complex formation between Fe (III) and picrate anion in the presence of piroxicam, as a complexing agent. Dispersive liquid–liquid microextraction (DLLME) was applied to extract the formed ion associate, Fe (III)-piroxicam. The absorbance of the extracted iron in the sedimented phase was measured by UV–Vis spectrophotometry. Two statistical methods of response surface methodology and genetic algorithm (GA) based on artificial neural network (ANN) were employed for prediction and optimization of a four-constituent DLLME. Plackett–Burman design was used for screening the influential parameters including pH, the volume of picrate anion, disperser, and extraction solvents. Central composite design (CCD) was used to obtain the optimum levels in the proposed method. The experimentally obtained
Researchers Elham Alian (First researcher)
abolfazl semnani (Second researcher)
Alireza Firooz (Third researcher)
Mahboube Shirani (Fourth researcher)
behnaz azmoon (Fifth researcher)