Abstract

To differentiate white wines from Croatian indigenous varieties, volatile aroma compounds were isolated by headspace solid-phase microextraction (HS-SPME) and analyzed by comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GC×GC-TOF-MS) and conventional one-dimensional GC-MS. The data obtained were subjected to uni- and multivariate statistical analysis. The extra separation ability of the GC×GC second dimension provided additional in-depth volatile profile information, with more than 1000 compounds detected, while 350 were identified or tentatively identified in total by both techniques, which allowed highly efficient differentiation. A hundred and sixty one compounds in total were significantly different across monovarietal wines. Monoterpenic compounds, especially α-terpineol, followed by limonene and linalool, emerged as the most powerful differentiators, although particular compounds from other chemical classes were also shown to have notable discriminating ability. In general, Škrlet wine was the most abundant in monoterpenes, Malvazija istarska was dominant in terms of fermentation esters concentration, Pošip contained the highest levels of particular C13-norisoprenoids, benzenoids, acetates, and sulfur containing compounds, Kraljevina was characterized by the highest concentration of a tentatively identified terpene γ-dehydro-ar-himachalene, while Maraština wine did not have specific unambiguous markers. The presented approach could be practically applied to improve defining, understanding, managing, and marketing varietal typicity of monovarietal wines.

Highlights

  • Aroma is among the most important attributes that drive the perception of wine sensory quality and varietal typicity by consumers

  • The aim of this study was to utilize the potential of two-dimensional gas chromatography with time-of-flight mass spectrometry (GC×GC-time-of-flight mass spectrometer (TOF-MS)) technique, in combination with headspace solid-phase microextraction (HS-SPME) and multivariate statistical tools, as a more efficient approach to characterize and differentiate monovarietal white wines based on their volatile aroma compound composition

  • Major volatile aroma compounds determined by GC-MS are listed in Table 1, grouped according to chemical class, and sorted within each class in order of decreasing F-ratio obtained by one-way ANOVA

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Summary

Introduction

Aroma is among the most important attributes that drive the perception of wine sensory quality and varietal typicity by consumers. The knowledge on the volatile aroma compound composition of monovarietal wines is important since it may enable producers to better cope with the phenomena encountered in production and to manage vinification with greater efficiency, all in order to produce high quality wines of accentuated varietal typicity. It may enable detailed and precise description of the aroma of monovarietal wines, which could be used in their marketing, especially towards informed consumers interested in wines of high quality with marked diversity and identity. Control in terms of varietal origin authentication is needed: the general strategy used by many research groups includes the (semi)quantification of a large number of volatile compounds in large sets of wines and use of the generated data for the production of multivariate statistical models able to classify wines, as well as to predict and confirm their varietal origin [5]

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