Application of genetic algorithm for baseline optimization in standard addition voltammetry

A new procedure of baseline correction in voltammetry which utilizes genetic algorithm and spline functions is presented. According to this method the background shape is modeled by the application of the approach which operates on natural selection phenomena. The optimization criterion is constructed with the usage of the three parameters of the voltammogram: peak’s height, shape of the peak base and linearity of the calibration model. Splines are used in approximation of the background because they enable to reproduce various baseline shapes. The procedure is performed automatically with minimum attention from the operator. The usefulness of the proposed approach is demonstrated on simulated voltammograms and Zn(II) signals registered in the rat’s brain microdialysate samples. Standard addition calibration is considered because it is especially sensitive to improper baseline approximation.

► Background is a relevant problem in interpretation of the voltammetric signals, especially in standard additions calibration.
► Most of the baseline correction approaches require manual operations which are not easy and frequently inconvenient.
► In this paper we propose multithreaded, automatic procedure, based on the genetic algorithms and the splines.
► The procedure may be performed automatically with minimum attention from the operator.
► The usefulness of the proposed approach is demonstrated on simulated voltammograms and Zn(II) signals.