2 resultados para Vehicle counting and classification

em Repositório Digital da UNIVERSIDADE DA MADEIRA - Portugal


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Thirty-six Madeira wine samples from Boal, Malvazia, Sercial and Verdelho white grape varieties were analyzed in order to estimate the free fraction of monoterpenols and C13 norisoprenoids (terpenoid compounds) using dynamic headspace solid phase micro-extraction (HS-SPME) technique coupled with gas chromatography–mass spectrometry (GC–MS). The average values from three vintages (1998–2000) show that these wines have characteristic profiles of terpenoid compounds. Malvazia wines exhibits the highest values of total free monoterpenols, contrary to Verdelho wines which had the lowest levels of terpenoids but produced the highest concentration of farnesol. The use of multivariate analysis techniques allows establishing relations between the compounds and the varieties under investigation. Principal component analysis (PCA) and linear discriminant analysis (LDA) were applied to the obtained matrix data. A good separation and classification power between the four groups as a function of their varietal origin was observed.

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Boal, Malvasia, Sercial and Verdelho are the main white grape varieties used in Madeira wine production. To estimate the free fraction of varietal aroma compounds of these varieties, 39 samples of musts were analysed to determine their content of monoterpenols and C13 norisoprenoids (terpenoids), using dynamic headspace solid-phase microextraction coupled with gas chromatography–mass spectrometry. The r-values for linearity studies of the analytical method used, varied between 0.977 (nerolidol) and 0.999 (linalool). The repeatability for each compound varied between 2.5% (citronellol) and 11.8% (β-ionone). The mean values from three vintages (1998, 1999 and 2000) confirmed that these musts have differentiated contents of terpenoids. In opposition to Verdelho musts, Malvasia showed the highest free terpenoids content. In order to establish relations between the compounds and the varieties under investigation, principal component analysis and linear discriminant analysis were applied to the data, revealing a good separation and classification power between the four groups as a function of varietal origin.