TY - JOUR
T1 - Classification of Nebbiolo-based wines from Piedmont (Italy) by means of solid-phase microextraction-gas chromatography-mass spectrometry of volatile compounds
AU - Marengo, Emilio
AU - Aceto, Maurizio
AU - Maurino, Valter
PY - 2002/1/11
Y1 - 2002/1/11
N2 - Sixty-eight samples of wines from Piedmont (Italy) were analysed to determine their content of volatile compounds, using the solid-phase microextraction (SPME) technique coupled with gas chromatography-mass spectrometry (GC-MS). Samples were from five groups of wines: Barolo, Barbaresco, Nebbiolo d'Alba, Roero and Langhe Nebbiolo, all produced from the Nebbiolo grape in the Langhe and Roero areas (province of Cuneo, Piedmont) but differing in vintage (respectively, 3 years, 2 years, 1 year, 8 months and few months) and production zone. Thirty-five analytes were identified; peak area data, corrected for internal standard, were used for pattern recognition treatments. Principal components analysis, hierarchical cluster analysis, Kohonen self organising map, stepwise linear discriminant analysis and soft independent modelling of class analogy were applied to the data, revealing a good separation between the five groups. A main factor, strictly connected to wine vintage, was identified and found to be related to some analytes.
AB - Sixty-eight samples of wines from Piedmont (Italy) were analysed to determine their content of volatile compounds, using the solid-phase microextraction (SPME) technique coupled with gas chromatography-mass spectrometry (GC-MS). Samples were from five groups of wines: Barolo, Barbaresco, Nebbiolo d'Alba, Roero and Langhe Nebbiolo, all produced from the Nebbiolo grape in the Langhe and Roero areas (province of Cuneo, Piedmont) but differing in vintage (respectively, 3 years, 2 years, 1 year, 8 months and few months) and production zone. Thirty-five analytes were identified; peak area data, corrected for internal standard, were used for pattern recognition treatments. Principal components analysis, hierarchical cluster analysis, Kohonen self organising map, stepwise linear discriminant analysis and soft independent modelling of class analogy were applied to the data, revealing a good separation between the five groups. A main factor, strictly connected to wine vintage, was identified and found to be related to some analytes.
KW - Statistical methods
KW - Volatile compounds
KW - Wine
UR - http://www.scopus.com/inward/record.url?scp=0037059576&partnerID=8YFLogxK
U2 - 10.1016/S0021-9673(01)01421-2
DO - 10.1016/S0021-9673(01)01421-2
M3 - Article
SN - 0021-9673
VL - 943
SP - 123
EP - 137
JO - Journal of Chromatography A
JF - Journal of Chromatography A
IS - 1
ER -