Multivariate data visualization methods based on elemental analysis of wines by atomic absorption spectrometry
Author(s) -
Slavica Ražić,
Djuro Čokeša,
Snežana Sremac
Publication year - 2007
Publication title -
journal of the serbian chemical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.227
H-Index - 45
eISSN - 1820-7421
pISSN - 0352-5139
DOI - 10.2298/jsc0712487r
Subject(s) - graphite furnace atomic absorption , principal component analysis , multivariate statistics , chemistry , mass spectrometry , atomic absorption spectroscopy , analytical chemistry (journal) , cluster (spacecraft) , hierarchical clustering , environmental chemistry , chromatography , computer science , cluster analysis , mathematics , statistics , physics , quantum mechanics , programming language
The contents of five metals (Cu, Mn, Fe, Cd, and Pb) in several red and white wines originating from different regions of Serbia were determined by flame and graphite furnace atomic absorption spectrometry. The data were processed us- ing chemometric techniques. Principal component and factor analysis were applied in order to highlight the relations between the elements and, after data reduction, three main factors controlling variability were identified. Application of hierarchical cluster analysis to the studied wines indicated differentiation of the samples belonging to different origins. No discrimination between red and white wines was found.
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