Mean polymerization degree of proanthocyanidins of grape seeds, skins and wines from Agiorgitiko (cv. Vitis vinifera): Differences among vintages

Grape canes are a non-recycled byproduct of wine industry (1-5 tons per hectare per year) containing valuable phytochemicals of medicine and agronomical interest. Resveratrol and wine polyphenols are known to exert a plethora of health-promoting effects including antioxidant capacity, cardioprotection, anticancer activity, anti-inflammatory effects, and estrogenic/antiestrogenic properties (Guerrero et al. 2009). Additionally, resveratrol is a major phytoalexin produced by plants in response to various stresses and promotes disease resistance (Chang et al. 2011). Our project aims to develop polyphenol-rich grape cane extracts to fight phytopathogenic or clinically relevant fungi. We initiate the project with the development of analytical methods to analyze resveratrol mono- and oligomers (dimers, trimers and tetramers) from grape canes and we evaluate their potential activity against clinically relevant opportunistic fungal pathogens (Houillé et al. 2014).

Despite the extensive research performed during the last decades, the multifactorial mechanism responsible for the white wine protein haze formation is not fully characterized. Herein, a new model is proposed, which is based on the experimental identification of sulfur dioxide as a major modulating factor inducing wine protein haze upon heating. As opposed to other reducing agents, such as 2-mercaptoethanol, dithiothreitol and tris(2-carboxyethyl)phosphine hydrochloride (TCEP), the addition of SO2 to must/wine upon heating cleaves intraprotein disulfide bonds, hinders thiol-disulfide exchange during protein interactions and can lead to the formation of novel inter/intraprotein disulfide bonds. Those are eventually responsible for wine protein aggregation which follows a nucleation-growth kinetic model as shown by dynamic light scattering [1].

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.

Vitis vinifera is one of the most diffused grapevines over the word and it is the raw material for high quality wines production. The availability of more resistant interspecific hybrid vine varieties, developed from crosses between Vitis vinifera and other Vitis species, has generating much interest, also due to the low environmental effect of production. However, hybrid grape wine composition and varietal differences between interspecific hybrids are not well defined. Different studies revealed that wine consumption has health effects due to its high content of antioxidants, as phenolic compounds. In particular, simple phenols are appreciated not only for their physiological health benefits, including antioxidant, anti-inflammatory and cardioprotective effects, but also because they affect wines organoleptic profile and have a significant role in defining their nutritional characteristics.

The present work contributes by developing a rapid sensory-directed methodology for the screening and selection of high quality wines with different sensory profiles Therefore, Verdejo and Tempranillo musts were fermented with 50 different yeasts each under controlled laboratory conditions. Resulting samples were firstly categorized according to five levels of quality by a panel of wine professionals (Sáenz-Navajas, Ballester et al. 2013). Higher quality samples were described by flash profiling by a semi-trained panel
(Valentin, Chollet et al. 2012) and most distinctive samples were screened by gas chromatography-olfactometry (GC-O) (López, Aznar et al. 2002).