Multivariate analysis for the classification and differentiation of Madeira wines according to main grape varieties

被引:94
作者
Câmara, JS
Alves, MA
Marques, JC
机构
[1] Univ Madeira, Dept Quim, Ctr Quim Madeira, P-9000390 Funchal, Portugal
[2] Univ Porto, Fac Engn, Depto Enga Quim, P-4099 Oporto, Portugal
关键词
wine; volatile compounds; HS-SPME/GC-MS analysis; PCA; SLDA;
D O I
10.1016/j.talanta.2005.08.012
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
In order to differentiate and characterize Madeira wines according to main grape varieties, the volatile composition (higher alcohols, fatty acids, ethyl esters and carbonyl compounds) was determined for 36 monovarietal Madeira wine samples elaborated from Boal, Malvazia, Sercial and Verdelho white grape varieties. The study was carried out by headspace solid-phase microextraction technique (HS-SPME), in dynamic mode, coupled with gas chromatography-mass spectrometry (GC-MS). Corrected peak area data for 42 analytes from the above mentioned chemical groups was used for statistical purposes. Principal component analysis (PCA) was applied in order to determine the main sources of variability present in the data sets and to establish the relation between samples (objects) and volatile compounds (variables). The data obtained by GC-MS shows that the most important contributions to the differentiation of Boal wines are benzyl alcohol and (E)-hex-3-en-1-ol. Ethyl octadecanoate, (Z)-hex-3-en-1-ol and benzoic acid are the major contributions in Malvazia wines and 2-methylpropan-1-ol is associated to Sercial wines. Verdelho wines are most correlated with 5-(ethoxymethyl)-furfural, nonanone and cis-9-ethyidecenoate. A 96.4% of prediction ability was obtained by the application of stepwise linear discriminant analysis (SLDA) using the 19 variables that maximise the variance of the initial data set. (c) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码:1512 / 1521
页数:10
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