Genetic Algorithms-Based Approach for Wavelength Selection in Simultaneous Spectrofluorimetric Determination of Ofloxacin and Riboflavin in biological samples by Partial Least-Squares

Abstract

This study shows that genetic algorithm (GA) is a suitable method for selecting wavelengths for partial least squares (PLS) calibration of mixtures with almost identical spectra without loss of prediction capacity employing spectrofluorimetric method. A training set of mixtures containing different concentrations of ofloxacin (OFL) and riboflavin (B2) were prepared to be used as calibration set to check the prediction ability of GA-PLS models due to spectral overlapping of these constituents. Each model was validated using a validation set and then real samples were analyzed. Linear calibration curves were obtained in the 0.5-5.0 and 2.0-10.0 µg mL-1 range for ofloxacin and riboflavin, respectively. To preprocess the data matrices, the orthogonal signal correction (OSC) was used and the analysis results were statistically compared. The methods accuracy for simultaneous determination of ofloxacin and riboflavin, were evaluated by the root mean square errors of prediction (RMSEP) which were 0.0868 and 0.158 for ofloxacin and riboflavin, respectively, and relative standard error of prediction (RSEP) which were 2.738 and 2.846 for ofloxacin and riboflavin, respectively using OSC-GA-PLS models. This procedure allows the simultaneous determination of OFL and B2 in human urine and serum samples with good reliability of the determination.