Wavelength selection for the determination of glucose in human serum by near-infrared spectroscopy

Physics

Scientific paper

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Infrared And Raman Spectroscopy

Scientific paper

A genetic algorithm (GA)-based wavelength selection procedure is developed to allow joint optimization of near-infrared wavelengths used and the number of latent variables employed in building partial least-squares calibration models for the determination of glucose in human serum samples. The random selection of a small number of initial wavelengths is found to decrease the number of final wavelengths selected dramatically. The effect of spectral resolution on the wavelength selection is also evaluated.

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