Vite e territorio. Il caso della Franciacorta nel medioevo

La caractérisation des terroirs viticoles est traditionnellement basée sur des descripteurs de la géologie et de la pédologie des différents milieux rencontrés, couplées à des données climatiques

Interspecific hybrid winegrapes are of growing interest in the context of climate change based on their disease resistance and cold hardiness. In addition to a need for increased understanding of their chemical composition, there is little empirical evidence on the consumer perception of non-vinifera wine. Phenolic compounds, and particularly color, play an important organoleptic and quality determination role in wine, but can vary significantly in interspecific hybrid wines compared to wines produced from Vitis vinifera cultivars [1, 2, 3]. Anecdotally, the variation in anthocyanin species, interactions, and concentrations in interspecific hybrids could result in a variance from“vinifera-like” wine color.

The last step in winemaking is packaging the wines for market placement, while preserving the quality attained during vinification. Since the 1980s, 2,4,6-trichloroanisole (TCA) has been recognised as an incidental and random contaminant of cork, with its migration into wine thought to contribute to ‘cork taint’. This molecule is not a cork component and little is known about how it is formed on trees. Its formation from the chlorine used to wash the cork stoppers, long suspected, has been excluded by the abandonment of chlorine washing.

Apart from pro(antho)cyanidins and tannins, other phenolic compounds in wine or grapes have been shown to interact with salivary proteins and may contribute to overall sensory in-mouth sensations [1, 2]. Anthocyanins are the dominant phenolics in red wine and grape skin [3] , so it is expected that they come into contact and interact with salivary proteins after ingestion.

It is fundamental for wineries to know the potential yield of their vineyards as soon as possible for future planning of winery logistics. As such, non-invasive image-based methods are being investigated for early yield prediction. Many of these techniques have limitations that make it difficult to implement for practical use commercially. The aim of this study was to assess whether yield can be estimated using images taken in-field with a smartphone at different phenological stages.