Genetic algorithm-based wavelength selection in multicomponent spectrophotometric determination by PLS: Application on sulfamethoxazole and trimethoprim mixture in bovine milk

Abstract

The simultaneous determination of sulfamethoxazole (SMX) and trimethoprim (TMP) mixtures in bovine milk by spectrophotometric method is a difficult problem in analytical chemistry, due to spectral interferences. By means of multivariate calibration methods, such as partial least square (PLS) regression, it is possible to obtain a model adjusted to the concentration values of the mixtures used in the calibration range. Genetic algorithm (GA) is a suitable method for selecting wavelengths for PLS calibration of mixtures with almost identical spectra without loss of prediction capacity using the spectrophotometric method. In this study, the calibration model based on absorption spectra in the 200-400 nm range for 25 different mixtures of SMX and TMP Calibration matrices were formed form samples containing 0.25-20 and 0.3-21 ?g mL-1 for SMX and TMP, at pH=10, respectively. The root mean squared error of deviation (RMSED) for SMX and TMP with PLS and genetic algorithm partial least square (GAPLS) were 0.242, 0.066 ?gmL-1 and 0.074, 0.027 ?g mL-1, respectively. This procedure was allowed the simultaneous determination of SMX and TMP in synthetic and real samples and good reliability of the determination was proved.