Chapter 4 - Chemometrics Applied to Food Control

Abstract

In this chapter, we present the basic principles of some linear and nonlinear chemometric methods applied in quality control and biosecurity of food. For linear methods, applications are addressed using principal component analysis (PCA), partial least squares (PLS) and partial least squares with discriminant analysis (PLS-DA). In the nonlinear methods, self-organizing maps (SOM), support vector regression (SVR) and support vector classification (SVC) are covered. Thus, exploratory analysis, regression, and classification problems are presented for both linear as for nonlinear approaches. In addition, some insight about data preparation and model validation using figures of merit will be provided.