Calibration transfer employing univariate correction and robust regression

Abstract

This paper proposes a new method for calibration transfer, which was specifically designed to work with isolated variables, rather than the full spectrum or spectral windows. For this purpose, a univariate procedure is initially employed to correct the spectral measurements of the secondary instrument, given a set of transfer samples. A robust regression technique is then used to obtain a model with low sensitivity with respect to the univariate correction residuals. The proposed method is employed in two case studies involving near infrared spectrometric determination of specific mass, research octane number and naphthenes in gasoline, and moisture and oil in corn. In both cases, better calibration transfer results were obtained in comparison with piecewise direct standardization (PDS). The proposed method should be of a particular value for use with application-targeted instruments that monitor only a small set of spectral variables.