Classification Of Brazilian Vinegars According To Their 1h Nmr Spectra By Pattern Recognition Analysis

This work describes using 1H NMR data and pattern recognition analysis to classify vinegars. Vinegar authenticity is linked to raw ingredient source and manufacturing conditions. Application of PCA and HCA methods resulted in the natural clustering of the samples according to the raw material used. Wine vinegars were characterized by a high concentration of ethyl acetate, glycerol, methanol and tartaric acid, while glycerol and ethyl acetate signals were not visible in alcohol/agrin vinegars. Apple vinegars showed to be richer in alanine. The KNN, SIMCA and PLS-DA methods were used to build predictive models for classification of vinegar type wine, apple and alcohol/agrin (27 samples - 22 as training set). The models were tested using an independent set (5 samples), no samples were wrongly classified. Validated models were used to predict the class of 21 commercial samples, which, as expected, were correctly classified. Eight commercial vinegars (honey, orange, pineapple and rice) were discriminated from these samples using PCA method. Honey vinegars did not present ethanol signals and pineapple vinegars presented the largest amount of tartaric acid. Rice and orange vinegars are richer in lactic acid and did not present the methanol signal. Alanine signals were not visible in orange vinegars. © 2009 Elsevier Ltd. 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Identification Of Components Of Brazilian Honey By 1h Nmr And Classification Of Its Botanical Origin By Chemometric Methods

The potential of NMR spectroscopy to differentiate honeys concerning to the nectar employed in its production was evaluated. The application of chemometric methods to 1H NMR spectra has allowed to discriminate the honeys produced in the state of São Paulo, being identified the signals of responsible substances for the discrimination. Application of PCA and HCA methods to 1H NMR data have resulted in the natural clustering of the samples. Wildflower honeys were characterized by higher concentration of phenylalanine and tyrosine. Citrus honeys showed higher amounts of sucrose than other compounds, while eucalyptus honeys had higher amount of lactic acid than the others. Assa-peixe honeys showed spectra similar to eucalyptus and citrus. Sugar-cane honeys showed some signals similar to eucalyptus and citrus honeys, but also showed the tyrosine and phenylalanine signals. Adulterated honeys showed 5-hydroxymethylfurfural, citric acid and ethanol signals. KNN, SIMCA and PLS-DA methods were used to build predictive models for honey classification. 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