Application of Chemometrics in the Food Sciences

Research works in the fields of Food Sciences are typically characterized by an elevated level of complexity, which reflects the multifaceted complexity of food matrices, transformations, processes and related phenomena. To properly address the study of data associated, the application of multivariate methods is definitely appropriate and functional. The present review article describes the main chemometric methods applied in the Food Sciences, from multivariate design of experiments to multivariate data analysis; this latter branch includes both unsupervised tools—such as exploratory analysis—and supervised techniques, usually applied to provide qualitative and quantitative predictive models. An overview of the principal applications of multivariate methods to food problems is critically presented and discussed, examining the scientific literature of the 2008–18 period.