Improvement of direct calibration in spectroscopy

Abstract

Several linear calibration methods have been proposed for predicting the concentration of a particular compound from a spectrum. Some methods are based on experimental data, such as Partial Least Square Regression. Other methods are based on expert data, e.g. Direct Calibration. This article proposes a new method, called Improved Direct Calibration, which uses expert and experimental information. It performs a projection onto the pure interest spectrum, after correcting it from influence factors. No calibration dataset is necessary to build this model. This method has been successfully applied to the quantification of ethanol in musts during fermentation, using near infrared spectrometry.