Multivariate prototype approach for authentication of food products

UMR Sciences pour l'Oenologie, INRA, 34060, Montpellier, France; Unité de Sensométrie et de Chimiométrie, ENITIAA/INRA, 44322, Nantes Cedex, France
Chemometrics and Intelligent Laboratory Systems (Impact Factor: 2.38). 03/2007; 87(2). DOI: 10.1016/j.chemolab.2007.01.003

ABSTRACT Authentication basically consists in deciding if a given unknown product belongs or not to a group of interest, defined by producers or regulators. More often, in order to demonstrate the authentication ability of a given instrumental analysis, several other groups are arbitrarily chosen. Then a Factorial or Linear Discriminant Analysis (FDA or LDA) or a Partial Least Squares Discriminant Analysis (PLS-DA) is usually performed; the model therefore depends on the nature of all observed groups of the study. The aim of this paper was to investigate an approach, named "prototype approach", based on a model built up only using the group of products of interest. Such an approach has the advantage not to depend on the whole complementary data of the study. Prototype approach is inspired by Multivariate Statistical Process Control and Hotelling T 2 statistic and consists in buiding up the assignment model according to the group of interest. Then, authentication step of new data is performed. Prototype approach and FDA were compared on a case study (authentication of Beaujolais red wines using their polyphenolic composition). False negative (#FN) and false positive (#FP) numbers were estimated by bootstrapping procedures for both methods. Compared to FDA, the prototype approach gave higher #FP with larger variability and lower #FN with lower variability. Wines produced with the same grape variety as AOC Beaujolais but in other regions were poorly authenticated. The prototype approach appears to be more flexible than FDA. The user can adjust the theoretical α risk in relation to its strategy, making that decision tool an alternative to discriminant analyses for authentication.

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