Multi-spectrometer calibration transfer based on independent component analysis

Abstract

Calibration transfer is indispensable for practical applications of near infrared (NIR) spectroscopy due to the need for precise and consistent measurements across different spectrometers. In this work, a method for multi-spectrometer calibration transfer is described based on independent component analysis (ICA). A spectral matrix is first obtained by aligning the spectra measured on different spectrometers. Then, by using independent component analysis, the aligned spectral matrix is decomposed into the mixing matrix and the independent components of different spectrometers. These differing measurements between spectrometers can then be standardized by correcting the coefficients within the independent components. Two NIR datasets of corn and edible oil samples measured with three and four spectrometers, respectively, were used to test the reliability of this method. The results of both datasets reveal that spectra measurements across different spectrometers can be transferred simultaneously and that the partial least squares (PLS) models built with the measurements on one spectrometer can predict that the spectra can be transferred correctly on another.