La région viticole Cotnari (Roumanie) et ses vins dans l’ensemble des grandes régions viticoles européennes

Nei vini rosati, è il colore ad avere il primo impatto con il consumatore. Esso risulterà tanto più accattivante, quanto più elegante e raffinato si presenta.

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During oak wood contact, wine undergoes important modifications that modulate its organoleptic quality and complexity, including its aroma, structure, astringency, bitterness and color. Vescalagin and castalagin are the two main C-glucosidic ellagitannins found in oak wood used for wine aging wood but lyxose/xylose derivatives (grandinin and roburin e) and dimeric forms (roburins a,b, c and d) are also present. The presence of several hydroxyl groups in the ortho-positions at the periphery of the structure of the ellagitannin isomers allows these molecules to undergo oxidation or condensation reactions with other compounds.

Hanseniaspora vineae (Hv) is a fermenting non-Saccharomyces yeast that compared to Saccharomyces cerevisiae (Sc) present some peculiar features on its metabolism that make it attractive for its use in wine production. Among them, it has been reported a faster yeast lysis and release of polysaccharides, as well as increased ß-glucosidase activity. Hv also produces distinctive aroma compounds, including elevated levels of fermentative compounds such as ß-phenylethyl acetate and norisoprenoids like safranal. However, it is known for its high nutritional requirements, resulting in prolonged and sluggish fermentations, even when complemented with Sc strain and nutrients.

The need to rationalize agricultural inputs has recently increased interest in assessing vineyard variability in order to implement variable rate input applications, so-called ‘precision viticulture’. In many viticultural areas globally, precision viticulture is already widely used such as for selective harvesting and variable rate application (VRA) of inputs such as irrigation and/or fertilizer. Robust VRA relies on having a geostatistically accurate map (of one or more vineyard attributes) requiring high sampling densities, which can be cost- and time-prohibitive to obtain. Previous work on spatial interpolation using kriging have upscaled ground-based measurements, but such upscaling strategies are applicable only when vineyard conditions are spatially continuous and satisfies the assumption of second-order stationary processes. Alternatively, mixed models that combine kriging and auxiliary information, such as the regression kriging (RK) method, are more instructive for spatial predictions. In order to improve prediction accuracies, it is therefore necessary to incorporate additional information to achieve accurate spatial patterns with low error.