Volatile Composition of Macedonian and Hungarian Wines Assessed by GC/MS

• Published in: Food and bioprocess technology Vol. 6; no. 6; pp. 1609 - 1617
• Main Authors: Ivanova, Violeta, Stefova, Marina, Vojnoski, Borimir, Stafilov, Trajče, Bíró, Ildiko, Bufa, Anita, Felinger, Attila, Kilár, Ferenc
• Format: Journal Article
• Language: English
• Published: New York Springer-Verlag 01.06.2013; Springer Nature B.V
• Subjects: Agriculture; Alcohols; Biotechnology; Chemical composition; Chemistry; Chemistry and Materials Science; Chemistry/Food Science; Communication; Composition; Dichloromethane; Esters; Ethanol; Fatty acids; Food Science; Gas chromatography; Lactones; Linalool; Mass spectrometry; Mass spectroscopy; Monoterpenes; Principal components analysis; Terpineol; Variance analysis; Volatile compounds; Wines; Wine; Liquid–liquid extraction; Volatile compounds; GC/MS
• ISSN: 1935-5130; 1935-5149
• DOI: 10.1007/s11947-011-0760-y

The volatile composition of eight varietal wines Vranec, Merlot, Cabernet Sauvignon, Temjanika and Chardonnay from the Republic of Macedonia, and Portugieser, Kékfrankos and Tokaji Aszú from Hungary has been characterized by means of gas chromatography/mass spectrometry technique. The wine volatile compounds were extracted in dichloromethane, and the extracts were concentrated under nitrogen. Forty-four volatile compounds have been identified mainly using the NIST mass spectral library and by comparison with the available standards used for quantification as well. Differences between the wines were noted for a number of compounds, such as a higher concentration of 1-pentanol and 2-phenyl ethanol in the red wines. Monoterpenes, linalool and terpineol were detected only in the white wines, Chardonnay and Tokaji. Macedonian red wines were characterized by a higher level of alcohols, while the Hungarian wines contained a higher amount of esters, fatty acids and lactones. A statistical treatment including one-way ANOVA, followed by a Tukey’s test has been performed in order to ascertain possible significant differences between the wines studied, and principal component analysis to study the possible grouping of the wines.