مشخصات پژوهش

A simple and sensitive spectrophotometric method to the simultaneous determination of Mn2 and Fe3 in foods, vegetable and water sample with the aid of artificial neural networks (ANNs) is described. It relies on the complexation of analytes with recently synthesised bis pyrazol base ligand as 4,40[(4-cholorophenyl) methylene] bis(3-methyl-1-phenyl-1H-pyrazol-5-ol)(CMBPP). The analytical data show that the ratio of ligand to metal in metal complexes is 1:1 and 1:2 for Fe3 and Mn2 , respectively. It was found that the complexation reactions are completed at pH 6.7 and 5 min after mixing. The results showed that Mn2 and Fe3 could be determined simultaneously in the range of 0.20–7.5 and 0.30–9.0 mg l1, respectively. The analytical characteristics of the method such as the detection limit and the relative standard error predictions were calculated. The data obtained from synthetic mixtures of the metal ions were processed by radial basis function networks (RBFNs) and feed forward neural networks (FFNNs). The optimal conditions of the neural networks were obtained by adjusting various parameters by trial-and-error. Under the working conditions, the proposed methods were successfully applied to the simultaneous determination of elements in different water, tablet, rice, tea leaves, tomato, cabbage and lettuce samples.