Il piano regolatore delle citta’ del vino: una metodologia di lavoro

The sustainability and authenticity of grape juice production have gained increasing attention, particularly regarding the environmental impact and health benefits of organic practices.

The global wine production is continuously evolving to meet the new demands and preferences of consumers. in this evolving scenario, it’s important to determine which trends will be short-lived and which will remain over time. The promotion of healthier habits has encouraged consumers to try to find alternatives with low or no alcohol content. The challenge for the industry is to produce an alcohol-free wine that retains the familiar aromas and mouthfeel of traditional wine but without alcohol. Ethanol is the most abundant compound in wine, excluding water.

Brandy de Jerez (BJ) is a spirit drink made exclusively from spirits and wine distillates and is characterized by the use of casks for aging that previously contained Sherries. The quality and sensory complexity of BJ depend on the raw materials and some factors: grape variety, conditions during processing the wine and its distillation, as well as the aging in the cask. Therefore, the original compounds of the grapes from which it comes are of great interest (1 y 2) being in most cases the Airén variety. Their relationship with the quality of the musts and the wines obtained from them has been studied (3) and varies each year of harvest depending on the weather conditions (4).

Le variabili meteorologiche e micro-meteorologiche ricoprono un importante ruolo sulla risposta vegeto-produttiva della vite e di conseguenza sulla qualità delle produzioni. Utilizzando una rete wireless di sensori sono stati monitorati i parametri meteorologici e micro-meteorologici di 4 vigneti del territorio toscano e in differenti condizioni di gestione agronomica.

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. The accuracy of the method for predicting bunch weight at different phenological stages was assessed for seven different varieties.