Transfer of Multivariate Calibrations between Four Near-Infrared Spectrometers Using Orthogonal Signal Correction

Abstract

The transfer of partial least squares (PLS) calibration models among four near-infrared spectrometers was investigated for the quantitative analysis of thermoset resin polymers. A comparative study of second derivatives, multiplicative scatter correction, finite impulse response filtering, slope and bias correction, model updating (MU), and orthogonal signal correction (OSC) was conducted to determine which processing methods achieved model transferability. It is shown that OSC and MU were superior to the other calibration transfer methods, leading to very robust PLS models with enhanced predictive ability. It is also shown that the transfer results obtained with OSC were not significantly different from those obtained with model updating.