Effect of Wavelength Drift on Single- and Multi-Instrument Calibration Using Genetic Regression

Abstract

The ability of genetic regression (GR) to correct for wavelength drift in instrument responses was investigated in single- and multiinstrument calibrations. Sample spectra of ternary mixtures were collected on two near-infrared (NIR) spectrometers, one a dispersive instrument and one a Fourier transform instrument, with different resolutions. In the first and second cases, calibration models were generated with the use of spectra collected on a single instrument. For the third case, hybrid calibration models (HCMs) were built in order to combine spectra from two instruments into one calibration model. In order to simulate a wavelength shift, some of the spectra were shifted along the wavelength axis from 0 nm to 6 nm. The performance of GR was poor when calibration models produced from unshifted spectra were used to predict shifted spectra. However, the inclusion of shifted spectra in the calibration model corrected the prediction of shifted and unshifted spectra at levels similar to those of models built and evaluated by using only unshifted spectra.