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The aim of this work is to evaluate the possibility of using 2D-NMR for the construction of classification models for balsamic vinegars of Modena. The goal was to obtain an indirect indicator of authenticity and a quality control tool. The spectral data were analyzed by chemometric methods, aiming to discriminate the samples in relation to their origin. Application of general discriminant analysis (GDA) revealed a good discrimination; the two obtained models explained 83.9% and 97.3% of the total variance with a predictive capacity of 98.6% and 98.4%, respectively. The signals of 5-HMF, β-glucose, 2,3-butanediol, 6-acetyl glucose, and different aliphatic signals of sugars were the most significant variables. These results are very promising for giving an important contribution in quality control and characterization of such very valuable foods.

Summary Volatile compounds from 90 Italian citrus honeys of different varieties (lemon, Citrus limon (L.) Burm., orange, Citrus sinensis (L.) Osbeck, and citrus, Citrus spp.), 30 provided by CRA-API (Consiglio per la Ricerca e la Sperimentazione in Agricoltura-Unita di ricerca di apicoltura e bachicoltura) (Bologna, Italy) and 60 purchased on the markets, were analysed to classify them according to the characteristic aroma profiles. A HS-SPME-GC method previously developed and validated was applied. Factor analysis and general discriminant analysis (GDA) were carried out on peaks and intensity data. Statistical analyses revealed a good separation between samples; the best model based on peaks data shows 66.5% and 33.5% of total variance explained by the first and the second canonical functions and a predictive capacity of 78.9%. Regarding the intensity data, the CFs of the GDA model explain 53.8% and 46.2% of the total variance and the crossvalidation shows a predictive capacity of 96.7%.

Summary Propolis has various biological activities closely related to the composition which varies according to environmental factors and also to the method of production. This study was aimed at determining whether or not HR-NMR and multivariate statistical analysis were able to classify propolis according to the method used to harvest it. Sixty propolis samples were analysed in all. The ethanolic propolis extracts were initially analysed for quantification of the main bioactive substances, balsams and waxes. The 1H NMR and heteronuclear multiple bond correlation spectra were then acquired. Spectral data were analysed by the application of multivariate statistical techniques (Factor Analysis and General Discriminant Analysis). The best results were obtained using the 1H NMR which furnishes a sufficiently effective model by analysing the spectral region between 4.50 and 13.00 ppm (predictive capacity: 96.7%).

Balsamic vinegar of Modena (BVM) and traditional balsamic vinegar of Modena (TBVM) are highly appreciated typical Italian products. The quality control and authentication assurance of both these balsamic vinegars are very important topics. In the recent years, the interest to develop new and standardized analytical procedures, able to further enhance the quality and commercial value of these typical and unique products and to preserve them from possible sophistications and adulterations, is increased. In this work, 76 samples of both BVM and TBVM were analyzed by 1 H NMR spectroscopy coupled with multivariate data analysis. The spectral data were analyzed by principal component analysis (PCA), general discriminant analysis (GDA) and classification tree analysis (CTA). The best and very promising model was obtained by a GDA which shows 98.6% of total variance explained by the first canonical function and a predictive capacity of 98.4% with a good separation between clusters. The signals of 5-HMF, α-glucopyranose, malic acid, succinic and acetic acids and the signal at 3.3 ppm were found to be the most statistically significant variables.

Lambrusco is a Protected Designation of Origin (PDO) red wine of Modena (Italy) produced according to the production regulation (Decreto Ministeriale (DM) July 27, 2009; GU no. 184-187-188, 13/08/2009). Here the use of (1)H NMR spectroscopy as molecular fingerprints of several PDO Lambrusco wines was proposed to serve as indicators of authenticity and quality control. Application of partial least squares discriminant analysis (PLS-DA) revealed a good varietal discrimination by analyzing the low-frequency spectral region. This model explains 68.8% of the variance for the Y vector (classification factor: varietal source). In particular, the signals of 2,3-butanediol, lactic, succinic and malic acids, and threonine were found to be the most statistically significant variables in the model. These findings seem to be very promising in the attempt to extend the study to geographical discrimination.