期刊
TRAC-TRENDS IN ANALYTICAL CHEMISTRY
卷 29, 期 3, 页码 234-245出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.trac.2009.11.008
关键词
Chemometrics; Classification; Cluster analysis; Compositional fingerprint; Discrimination; Instrumental assay; Modeling; Principal component analysis; Sensory property; Wine characterization
资金
- Spanish Ministerio de Ciencia y Tecnologia [CTQ2008-04776/BQU]
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.
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