Valutazione dell’equilibrio vegeto-produttivo con metodiche di proximal sensing

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.

Red grape pomace, a waste from wine production, can be valorised by extracting polyphenols, high-added value compounds used in cosmetics or oenology. For use at an industrial level, using green extraction techniques, pomace need to be stored before being processed. The aim of this study is to test various storage conditions in order to maintain high level of polyphenols over 180 days, while keeping storage cost economically interesting. In a first step, different storage conditions (ambient temperature or cooled (4°C) temperature, anaerobic (saturation with N2) or aerobic conditions, and addition of sulphur dioxide (SO2)) were compared on small samples (1 kg) packed in plastic pockets. The quality of storage was assessed by following the optical density of the pomace extract at 280 nm (DO 280 expressed as mg/l eq gallic acid), which is an indication of the amount of remaining extractable polyphenols.

Context and purpose. Nitrogen (N) is crucial for plant development but is used inefficiently, with only 30–40% of the fertilizer assimilated by crops, leading to significant environmental losses.

Under the pressure of global warming, several wine grape growing regions around the world are increasingly suffering from advanced and compressed phenology; endangering wine character while also creating serious logistic problems. From a physiological standpoint, the issue of delaying ripening is not simple as, in several instances, only a few processes must be delayed (i.e. sugar accumulation into the berries) while other events such as pigmentation and accumulation of other important phenolic compounds should proceed at a normal rate. Thus, the issue of decoupling technological maturity from phenolic maturity is another important consideration. Over the last decades, several research groups have endeavored to establish alternate cultural practices aimed at addressing this decoupling. In some cases, special applications of quite robust and well known practices regarding physiological principles have been utilized, however some completely new techniques are also being studied. In figure 1 of the review, we offer a panorama of the available tools and in the text we elaborate on those having provided most reliable and consistent results under an array of genotypes and environmental conditions. Among these, primary focus is given to post‐veraison—apical to the cluster—leaf removal (that can also be suitably replaced by applications of anti‐transpirants); the use of kaolin against multiple summers’ stresses; and a drastic version of late winter pruning having the potential to postpone ripening into a cooler period with improved grape composition and a limited negative impact on yield and storage reserves replenishment. 

Eugenol, widely spread in various plants notably cloves, basil and bay, was identified too in wines from hybrid grapes without contact with oak wood. This aromatic molecule presents a strong spicy note of clove and also antifongic properties. Eugenol was described as an endogenous compound of Baco blanc, from the grapes to the spirits of Armagnac area. Moreover, this compound is a chemical marker of Baco blanc products quality.
Influences of harvest time and different winemaking processes (settling, use of enzymatic preparations, lees content and stock time before distillation) on Baco blanc wine eugenol contents were explored using a two-levels full factorial Design of Experiments (DoEs).