Multivariate Calibration and Classification Modeling in Spectroscopy Applications

Abstract

The purpose of this thesis is to study the feasibility of building multivariate models based on miniaturized Fourier Transform Near-Infrared (FT-NIR) spectrometers, and determine the issues emerged and propose appropriate solutions for them. The thesis presents some classification models with di↵erent natures, and each model introduces a new challenge associated with our proposed handling, the models are textiles type classification, co↵ee classification according to ca↵eine level, species type classification and milk classification according to fat level models. In addition, the thesis presents two regression applications with commercial standards, namely, milk regression application and health care application.