Grasas y Aceites, Vol 53, No 1 (2002)

Chemometrics: From classical to genetic algorithms

Riccardo Leardi
Department of Pharmaceutical and Food Chemistry and Technology, University of Genova, Italy


In this paper the fundamentals of Chemometrics are presented, by means of a quick overview of the most relevant techniques for data display, classification, modeling and calibration. Two emerging techniques such as Genetic Algorithms and Artificial Neural Networks will also be presented. Goal of the paper is to make people aware of the great superiority of multivariate analysis over the commonly used univariate approach. Mathematical and algorithmical details are not presented, since the paper is mainly focused on the general problems to which Chemometrics can be successfully applied in the field of Food Chemistry.


Calibration; Chemometrics; Classification; Data display; Modeling; Multivariate analysis

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Copyright (c) 2002 Consejo Superior de Investigaciones Científicas (CSIC)

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