Food authenticity is a challenging analytical problem normally addressed using sophisticated laboratory methods which produce large data sets. Multivariate mathematical methods are required to process such data sets typically to answer a question such as “Is sample X, which claims to be of type A, compatible with type A samples on the basis of its analytical measurements?”. Class-modelling methods are recommended to answer this type of question and the principles, practice and results of several types of such methods are discussed. A comparison, in terms of advantages and short-comings, with the discriminant classification approach is also presented.

Multivariate class modeling for the verification of food-authenticity claims

OLIVERI, PAOLO;
2012-01-01

Abstract

Food authenticity is a challenging analytical problem normally addressed using sophisticated laboratory methods which produce large data sets. Multivariate mathematical methods are required to process such data sets typically to answer a question such as “Is sample X, which claims to be of type A, compatible with type A samples on the basis of its analytical measurements?”. Class-modelling methods are recommended to answer this type of question and the principles, practice and results of several types of such methods are discussed. A comparison, in terms of advantages and short-comings, with the discriminant classification approach is also presented.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/590943
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