Neuro-genetic approach for optimisation of the spectrophotometric catalytic determination of cobalt

A neuro-genetic approach was developed to optimise an automated procedure for the spectrophotometric determination of cobalt in bovine liver, fish and mussel samples by using a monosegmented flow system. The method exploited the Co(II) catalysed oxidation of Tiron by hydrogen peroxide. The values related to reagent concentrations and mean residence time were optimised in terms of slope and correlation coefficient of the calibration curve. The neural networks were used to model the system, relating the parameters of the monosegmented flow system with those of the calibration curve. The genetic algorithm was applied to attain the optimum values from the model developed by the neural networks. The detection and quantification limits were 1.66 and 5.33ngl-1 Co, respectively.