Merging fast sensory profiling with non-targeted GC-MS analysis for multifactorial experimental wine making

Protein haze in white wines is a major technological and economic problem of the wine industry. Field tests were carried out in steep slope vineyards planted with Riesling grapes over 3 dry growing seasons to study the effect of drought stress on the concentration of proteins in the resulting wines. Plots suffering from drought stress were compared with surrounding drip irrigated plots. Riesling grapes were processed into wines by conventional procedures. Protein amounts of the isolated wine colloids of the stressed samples were always higher than those of the watered samples(mean watered 13.8 ± 0.44, mean stressed 17.4 ± 0.40 g 100 g-1). As a consequence, higher bentonite doses were needed to achieve protein haze stability of the drought stressed treatments.

1,1,6-trimethyl-1,2-dihydronaphtelene (TDN) evokes the odor of “petrol” in wine, especially in the variety Riesling. Increasing UV-radiation due to climate change intensifies formation of carotenoids in the berry skins and an increase of TDN-precursors1. Exploring new viticultural and oenological strategies to limit TDN formation in the future requires precise knowledge of TDN thresholds in different matrices. Thresholds reported in the literature vary substantially between 2 µg/L up to 20 µg/L2,3,4 due to the use of different methods. As Riesling grapes are used for very different wine styles such as dry, sweet or sparkling wines, it is essential to study the impact of varying ethanol and carbonation levels.

Phenolic compounds are very important in crop plants and have been the subject of a large number of studies. Three main reasons can be cited for optimizing the level of phenolic compounds in crop plants: their physiological role in plants, their technological significance for food processing, and their nutritional characteristics1 Indeed, an enormous diversity of phenolic antioxidants is found in fruits and vegetables, and their presence and roles can be affected or modified by several pre- and postharvest cultural practices and/or food processing technologies (Ruiz-García et al. 2012, Goldman et al. 1999, Tudela et al. 2002). In winegrapes, the technological importance of phenolic compounds, mainly flavonoids, is well-known.

In general, there is a well-established lexicon related to wine aroma and taste properties; however mouth-feel-related vocabulary usually includes heterogeneous, multimodal and personalized terms. Gawel et al.
(2000) published a wheel related to mouthfeel properties of red wine. However, its use in scientific publications has been limited. The authors accepted that the approach had certain limitations as it included redundant and terms with hedonic tone and some others were absent. It is of high interest to generate a mouth-feel lexicon and finding the chemical compound or group of compounds responsible for such properties in red wine. In the present work a chemical fractionation method has been developed.

Yeast cells possess a cell wall comprising primarily glycoproteins, mannans, and glucan polymers. Several yeast phenotypes relevant for fermentation, wine processing, and wine quality are correlated with cell wall properties. To investigate the effect of wine fermentation on cell wall composition, a study was performed using mid-infrared (MIR) spectroscopy coupled with multivariate methods (i.e., PCA and OPLS-DA). A total of 40 yeast strains were evaluated, including Saccharomyces strains (laboratory and industrial) and non-Saccharomyces species. Cells were fermented in both synthetic MS300 and Chardonnay grape must to stationery phase, processed, and scanned in the MIR spectrum.