Regional features of northern Italian sparkling wines, identified using solid-phase micro extraction and comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry

被引:64
作者
Carlin, Silvia [1 ]
Vrhovsek, Urska [1 ]
Franceschi, Pietro [2 ]
Lotti, Cesare [1 ]
Bontempo, Luana [1 ]
Camin, Federica [1 ]
Toubiana, David [3 ]
Zottele, Fabio [4 ]
Toller, Giambattista [4 ]
Fait, Aaron [3 ]
Mattivi, Fulvio [1 ]
机构
[1] FEM, Res & Innovat Ctr, Dept Food Qual & Nutr, Via E Mach 1, I-38010 San Michele All Adige, Italy
[2] FEM, Res & Innovat Ctr, Biostat & Data Management, Via E Mach 1, I-38010 San Michele All Adige, Italy
[3] Ben Gurion Univ Negev, Jacob Blaustein Inst Desert Res, French Associates Inst Agr & Biotechnol Drylands, IL-84993 Sede Boqer, Israel
[4] FEM, Dept Expt & Technol Serv, Technol Transfer Ctr, Via E Mach 1, I-38010 San Michele All Adige, Italy
关键词
GCxGC-TOF-MS; Sparkling wines; Volatile compounds; Untargeted metabolomics; Traceability; Correlation-based network analysis; VOLATILE SULFUR-COMPOUNDS; HETEROCYCLIC ACETALS; GRAPE; AROMA; CLASSIFICATION; COMPONENTS; EVOLUTION; MODELS; ORIGIN; MUSCAT;
D O I
10.1016/j.foodchem.2016.03.112
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
We carried out comprehensive mapping of volatile compounds in 70 wines, from 48 wineries and 6 vintages, representative of the two main production areas for Italian sparkling wines, by HS-SPME-GCxGC-TOF-MS and multivariate analysis. The final scope was to describe the metabolomics space of these wines, and to verify whether the grape cultivar signature, the pedoclimatic influence of the production area, and the complex technology were measurable in the final product. The wine chromatograms provided a wealth of information, with 1695 compounds being found. A large number of putative markers influenced by the cultivation area was observed. A subset of 196 biomarkers fully discriminated between the two types of sparkling wines investigated. Among the new compounds, safranal and a-isophorone were observed. We showed how correlation-based network analysis could be used as a tool to detect the differences in compound behaviour based on external/environmental influences. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:68 / 80
页数:13
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