Journal
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
Volume 51, Issue 27, Pages 8055-8060Publisher
AMER CHEMICAL SOC
DOI: 10.1021/jf034851c
Keywords
wine; free amino acids; biogenic amines; chemometrics; principal component analysis; linear discriminant analysis
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Principal component analysis (PCA) and linear discriminant analysis (LDA) were used to classify 187 Hungarian white and red wines according to wine-making technology, geographic origin (wine-making region), grape variety, and year of vintage based on free amino acid and biogenic amine contents. Determination of free amino acids and biogenic amines was accomplished by ion-exchange chromatography. Six principal components accounted for >77% of the total variance in the data. The plots of component loadings showed significant groupings of free amino acids and biogenic amines. The component scores grouped according to wines made by different wine-making technologies. Using LDA the variables with a major discriminant capacity were determined. Almost complete classification (94.7%) was achieved concerning both white and red wines and wines made by different wine-making technologies. The results of differentiation between white wines according to geographic origin, grape variety, and year of vintage were 70.8, 62.4, and 73.5%, respectively. The same numbers for red wines according to geographic origin, grape variety, and year of vintage were 64.9, 71.6, and 82.4%, respectively.
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