Les activités peroxidasiques du raisin de quelques cépages de Roumanie

Oxidation processes constitute a main problem in winemaking. Oxidation result in color browning and varietal aroma loss, which are key attributes of wine organoleptic quality [1]. Despite the mechanisms involved in wine oxidation have been extensively reviewed [2], the protection of wine against oxidative spoilage remains one of the main goals of winemaking.
SO2 is one of the most efficient wine antioxidants used to prevent oxidation and microbial spoilage. However, intolerances caused by SO2 have led to the reduction of its concentration in wines.

Most oxidation reactions in wine require iron as a catalyst. The iron content of wine has decreased greatly in recent decades due to the use of low or no release cellar materials; however, in some cases it is still necessary to adopt winemaking practices to remove excess iron from wine, prevent its oxidation, and be able to reduce the addition of sulfur dioxide and other antioxidants.

Agriculture, natural resource management and the production and sale of products such as wine are increasingly data-driven activities. Thus, the use of remote and proximal crop and soil sensors to aid management decisions is becoming commonplace and ‘Agtech’ is proliferating commercially; mapping, underpinned by geographical information systems and complex methods of spatial analysis, is widely used. Likewise, the chemical and sensory analysis of wines draws on multivariate statistics; the efficient winery intake of grapes, subsequent production of wines and their delivery to markets relies on logistics; whilst the sales and marketing of wines is increasingly driven by artificial intelligence linked to the recorded purchasing behaviour of consumers. In brief, there is data everywhere!

Opinions will vary on whether these developments are a good thing. Those concerned with the ‘mystique’ of wine, or the historical aspects of terroir and its preservation, may find them confronting. In contrast, they offer an opportunity to those interested in the biophysical elements of terroir, and efforts aimed at better understanding how these impact on vineyard performance and the sensory attributes of resultant wines. At the previous Terroir Congress, we demonstrated the potential of analytical methods used at the within-vineyard scale in the development of Precision Viticulture, in contributing to a quantitative understanding of regional terroir. For this conference, we take this approach forward with examples from contrasting locations in both the northern and southern hemispheres. We show how, by focussing on the vineyards within winegrowing regions, as opposed to all of the land within those regions, we might move towards a more robust terroir zoning than one derived from a mixture of history, thematic mapping, heuristics and the whims of marketers. Aside from providing improved understanding by underpinning terroir with data, such methods should also promote improved management of the entire wine value chain.

ulfur compounds in wine have been studied for several years due to their impact on wine flavour, but the role of polysulfides is a recent topic. Polysulfides in wine are formed when two sulfhydryl groups oxidize, especially in presence of elemental sulfur or metal catalysts from field treatment residues (Ugliano et al. 2011). These compounds are odourless, but can degrade during storage and affect the wine quality. The mechanism of their formation is still largely unknown but different chemical and biochemical pathways have been suggested. Disulfides from cysteine (Cys) and glutathione (GSH) have been revealed in model wines (Kreitman et al. 2016) and more recently also higher polymerized forms in real wines (Van Leeuwen et al. 2020). Volatile varietal thiols like 3-mercaptohexanol (3MH) and 4-mercaptopentanone (4MMP) – flavour compounds with tropical or fruity notes – could undergo similar reactions, also with Cys and GSH, subsequently losing their flavour property (fate). Even more concerning is the possible release of H2S from polysulfides during storage, leading to undesired off-flavours (Sarrazin et al. 2010).

The selection of ancient grapevine varieties aims to achieve genetic gains in several important traits that can make the variety more interesting for the objectives of the producers. Traditionally, yield and quality traits of the must have been considered for selection, but many others can be taken into account. Linear mixed models are fitted to the data to predict the empirical best linear unbiased predictors (EBLUPs) of genotypic effects for each evaluated trait, which will be the basis for selection.