Elsevier

Journal of Chromatography A

Volume 1218, Issue 3, 21 January 2011, Pages 504-517
Journal of Chromatography A

Development of a sensitive non-targeted method for characterizing the wine volatile profile using headspace solid-phase microextraction comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry

https://doi.org/10.1016/j.chroma.2010.11.008Get rights and content

Abstract

Future understanding of differences in the composition and sensory attributes of wines require improved analytical methods which allow the monitoring of a large number of volatiles including those present at low concentrations. This study presents the optimization and application of a headspace solid-phase microextraction (HS-SPME) method for analysis of wine volatiles by comprehensive two-dimensional gas chromatography (GC × GC) time-of-flight mass spectrometry (TOFMS). This study demonstrates an important advancement in wine volatile analysis as the method allows for the simultaneous analysis of a significantly larger number of compounds found in the wine headspace compared to other current single dimensional GC–MS methodologies. The methodology allowed for the simultaneous analysis of over 350 different tentatively identified volatile and semi-volatile compounds found in the wine headspace. These included potent aroma compound classes such as monoterpenes, norisoprenoids, sesquiterpenes, and alkyl-methoxypyrazines which have been documented to contribute to wine aroma. It is intended that wine aroma research and wine sensory research will utilize this non-targeted method to assess compositional differences in the wine volatile profile.

Introduction

The fields of separation science and sensory science have advanced our knowledge of how volatile and semi-volatile compounds contribute to wine aroma [1], [2]. With more than 800 aroma compounds reported in the volatile fraction of wine [3], it is well understood that the wine volatile profile is complex. Some studies have concluded that the vast majority of wine volatile compounds have little or no aroma activity and that specific aroma profiles can be explained by relatively few aroma compounds [4]. However, there is conflicting evidence about the complexity of the system given that odor mixtures have masking (modification of the perceived odor), counteraction (reduction of the odor intensity) [5], and synergistic (complementation or enhancement of the odor intensity) [6] effects which play an important role in defining the perceived aroma of wine [7], [8]. It is thus important that grape and wine researchers develop the analytical capacity to measure as many volatiles as possible to enable better comparisons of effects of viticultural and winemaking studies and to identify candidate compounds that can be correlated with differences in the perceived aroma of wine.

The development of comprehensive two-dimensional gas chromatography (GC × GC) [9] has been followed by numerous reviews discussing the principals and experimental design of GC × GC [10], [11], [12]. These reviews have shown that GC × GC offers enhanced separation efficiency, reliability in qualitative and quantitative analysis, capability to detect low quantities, and information on the whole sample and its components. In more recent years, there has been a shift towards the use of this technique in the analysis of real-life samples including food and beverages, environmental, biological, and petrochemical [13].

A number of grape and wine profiling studies have used headspace solid-phase microextraction (HS-SPME) to better understand the role of various compounds in differentiating varieties, regions, and wine vintage [14], [15], [16] and the technique has been repeatedly documented as a sensitive, reproducible, automated method for pre-concentration of wine volatiles prior to analysis [17], [18], [19]. The combination of HS-SPME and GC × GC-TOFMS techniques has provided a major advantage in analyzing complex samples where the number of analytes may be large or the analytes of interest are present at trace levels – as is the case with wine. A number of publications have emerged in the grape and wine field that have utilized HS-SPME and GC × GC as a technique [20], [21], [22], [23], [24], [25], [26]. However, the majority of studies have used the method for targeted analysis [20], [22], [23], [24], [26] with only two publications to date utilizing the technique for volatile profiling [21], [25].

Rocha et al. [21] used GC × GC to analyze monoterpenes in grapes and identified 56 monoterpenes in the Fernão-Pires variety, of which 20 were reported for the first time in grapes. This highlighted the advantage that structured chromatographic separation can provide in compound classification and compound identity confirmation. There continues to be new aroma compound discoveries in the grape and wine research field with recent discoveries including (E)-1-(2,3,6-trimethylphenyl)buta-1,3-diene (TPB) [27] and 1(2H)-azulenone, 3,4,5,6,7,8-hexahydro-3,8-dimethyl-5-(1-methylethenyl)- ((−)-rotundone) [28]. It is anticipated that GC × GC will provide significant advantages in the identification of new and novel compounds which were previously unresolved using traditional one-dimensional chromatography.

A recent critical review [29] identified that future developments in understanding differences in the sensory attributes of wines will be due to: (1) development of improved and high throughput analytical methods that will allow monitoring of a large number of volatiles including those present at low concentrations; (2) improved understanding of the relationships between chemical composition and sensory perception, including an emphasis on the mechanisms of how odorants and matrix components interact chemically to impact odorant volatility and overall flavor perception of wines; and (3) multidisciplinary studies using genomic and proteomic techniques to understand flavor and aroma formation in the grape and during fermentation. The current study addresses the first recommendation from this publication and outlines a comprehensive analytical technique for the analysis of the wine volatile profile. The application of this technique to a small number of commercial wines clearly demonstrates that the optimized method can resolve and identify a large number of compounds and could be used in the future to differentiate wines based on their volatile profile.

Section snippets

Samples

Method development was conducted using a young (<12 months old) commercially available Cabernet Sauvignon wine (∼13.0% ethanol, v/v) from Australia. The wine was dispensed for use from a 2 L boxed wine bladder (cask) to minimize spoilage and oxidation during the course of analysis. Evaluation of the method was carried out using commercially available Cabernet Sauvignon wines with four wines from the 2005 vintage and one wine from the 2006 vintage representing four Western Australian Geographical

HS-SPME optimization

Although many compounds were identified, a representative selection of 25 target compounds, regarded as important contributors to wine aroma [1], [2], were used for HS-SPME method optimization. The SPME optimization results are discussed with reference to Cluster membership of compounds listed in Table 1.

Conclusions

The current study has described the development of a sensitive and comprehensive method for analyzing volatile and semi-volatile compounds found in the wine headspace through the use of HS-SPME/GC × GC-TOFMS. This study is the first to clearly show that the use of elevated temperatures during the incubation step of HS-SPME analysis of wine does generate artifacts. It is not intended that this method be used for high throughput or routine analysis of wine volatiles due to the higher costs

Acknowledgements

This research project was funded by Australia's grape growers and winemakers through their investment body the Grape and Wine Research and Development Corporation with matching funding from the Australian Federal Government. This work has been conducted as a collaboration between Murdoch University, CSIRO Plant Industry and The University of California, Davis with industry support provided by Houghton Wines. The authors would like to acknowledge that the GC × GC TOFMS was purchased through an

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