Characterization of wines using compositional profiles and chemometrics

被引：136

作者：

Saurina, Javier ^{[1
]}

机构：

[1] Univ Barcelona, Dept Analyt Chem, E-08028 Barcelona, Spain

来源：

TRAC-TRENDS IN ANALYTICAL CHEMISTRY | 2010年 / 29卷 / 03期

关键词：

Chemometrics; Classification; Cluster analysis; Compositional fingerprint; Discrimination; Instrumental assay; Modeling; Principal component analysis; Sensory property; Wine characterization; NEAR-INFRARED-SPECTROSCOPY; PATTERN-RECOGNITION ANALYSIS; HEADSPACE-MASS-SPECTROMETRY; TRANSFORM MIDINFRARED SPECTROMETRY; PERFORMANCE LIQUID-CHROMATOGRAPHY; FACE FLUORESCENCE SPECTROSCOPY; PRINCIPAL COMPONENT ANALYSIS; MULTIVARIATE DATA-ANALYSIS; BAR SORPTIVE EXTRACTION; CANARY-ISLANDS SPAIN;

D O I：

10.1016/j.trac.2009.11.008

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

This review discusses strategies for characterizing wines based on compositional profiles as sources of information. Contents of low molecular organic acids, volatile species, polyphenols, amino acids, biogenic amines and inorganic species seem to depend on climatic, agricultural and wine-making factors. As a result, compositional profiles of these families of natural wine components can be exploited as potential descriptors of wine and its quality. Most characterization studies rely on chemometrics to facilitate extraction of information. Cluster analysis, principal component analysis and related methods are currently used for discrimination, classification, modeling and correlation. (C) 2010 Elsevier Ltd. All rights reserved.

引用

页码：234 / 245

页数：12

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