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

• Type: Article in International Scientific Journal
• Date: 2006

Authors

Camara, JS (Author) Other; Alves, MA (Author) FEUP; Marques, JC (Author) Other

Journal

Title: Talanta

Vol. 68

Pages: 1512-1521

ISSN: 0039-9140

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 79 Citations

ISI Web of Science

Scopus - 102 Citations

Scientific classification

FOS: Natural sciences > Chemical sciences

Other information

Authenticus ID: P-004-N6X

DOI: 10.1016/j.talanta.2005.08.012

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 10