Characterization and discrimination of different aged 'Aceto Balsamico Tradizionale di Modena' products by head space mass spectrometry and chemometrics

Considering the complexity of this food matrix, due to its traditional making procedure, the obtained instrumental data have first been analysed by parallel factor analysis (PARAFAC), an extension of principal component analysis to higher order arrays, in order to visualise the 'natural' grouping of vinegar samples and to inspect producers similarity/dissimilarity. On the basis of the PARAFAC results a reasonable class partition with respect to ageing was accomplished and both linear discriminant analysis (LDA) and soft independent modelling of class analogy (SIMCA) were applied as classification tools. Furthermore, it has been shown that discrimination on age basis can be improved by using feature selection in the wavelet domain through WPTER algorithm.