Determination of number of significant components and key variables using genetic algorithms in liquid chromatography-nuclear magnetic resonance spectroscopy and liquid chromatography-diode array detection

A new method is proposed for determination of the number of significant components in hyphenated chromatographic data. The method is based on the application of genetic algorithms (GA). The method is applied to five datasets from on-flow liquid chromatography with nuclear magnetic resonance spectroscopy (LC-NMR) and on three datasets from liquid chromatography with diode array detector (LC-DAD). The effect of different factors such as the application of technique on time or spectral direction, noise level, baseline, chromatographic resolution and relative peak height has been studied. The method is compared with other chemometric approaches for rank analysis and variable selection. The results produced by GA are promising on both types of data.