[Curve fitting based on genetic algorithms for quantitative resolution in overlapped fluorescence spectra]

The exponentially modified Gaussian (EMG) model-based genetic algorithm was used as a fitness function for fitting fluorescence spectrogram. The method was effective for solving the interference of fluorescent substance in the course of the multi-component quantitative analysis. As an example, the interference of endogenous fluorophores in different urines with the fluorescence of gatifloxacin (GFLX) was examined. A good eradicating efficacy was achieved by using the fitting fluorescence spectrogram. Under the optimized experimental conditions, the good linear relationship between the fluorescence intensity and GFLX concentration was obtained in the range of 0.06-3.5 microg x mL(-1) with a correlation coefficient of 0.9994. The detection limit and recovery were 0.02 microg x mL(-1) and 99.2%-109.4%, respectively, with the relative standard deviation from 1.3% to 2.7%. The proposed fitting fluorescence spectrometric method was rapid, simple and highly sensitive for the determination of GFLX in different human urine without preseparation. The recovery, selectivity, linearity, precision and accuracy of the method are convenient for routine assays and pharmacokinetic studies.