Chemometric Characterisation of Basque and French Ciders according to their Polyphenolic Profiles

ALONSO-SALCES, R. M.; GUYOT, S.; HERRERO, C.; BERRUETA, L. A.; DRILLEAU, J. F.; GALLO, B.; VICENTE, F.

Helsinki (Finlandia)

Conferencia; XXII International Conference on Polyphenols; 2004

University of Helsinki and GroupePolyphénols

Polyphenolic composition of Basque and French ciders were determined by HPLC-DAD following thiolysis to characterise and differentiate these beverages by developing a classification system which confirm the authenticity of both kind of cider. A data set consisting of 165 cider samples and 27 features measured was evaluated using multivariate chemometric techniques such as cluster analysis and principal component analysis so as to perform a preliminary study of data structure. Supervised pattern recognition techniques such as linear discriminant analysis (LDA), K-nearest neighbours (KNN), soft independent modelling of class analogy (SIMCA) and multilayer feed-forward artificial neural networks (MLF-ANN) attained classification rules for the two categories based on the chemical data, which produced satisfactory results. Thus, an authentication system was proposed by combining two of the mentioned techniques: SIMCA and LDA or KNN models achieved 100% of hits, since LDA and KNN allow the detection of every Basque cider and SIMCA provided a model for Basque cider that exclude all French ciders. Cider polyphenolic profiles provided adequate information to develop classification rules for identifying ciders according to their geographical origin, the Basque Country or France. Chemical and organoleptic differences between these two types of cider are likely due to the original and distinctive cidermaking technologies used for their elaboration.