A new chemiluminescence method related to molecules derived from Botrytis cinerea for characterization of Aszu wines from Tokaj, from Hungary

AIM: High pressure technologies represent a promising alternative to thermal treatments for improving quality and safety of liquid foods.

There is a growing interest in the exploitation of vine-shoots waste, since they are often left or burned. Sánchez-Gómez et al. [1] have shown that vines-shoots aqueous extracts have significant contents of bioactive compounds, among which several polyphenols and volatiles are highlighted. Recent studied had demonstrated that the chemical composition of vine-shoots is enhanced when vine-shoots are toasted
[2,3]. The application of vegetable products in the vineyards has led to significant changes towards a more “Sustainable Viticulture”. An innovative foliar application for Airén vine-shoot extracts have been carried out to the vineyard. It has been shown that they act as grape biostimulants, improving certain wine quality characteristics [4].

SO2 is the most widely used preservative in the wine industry. However, there are several drawbacks related with the use of SO2 in wine such as its toxicity and the unpleasant odor in case of excess.

Grapevine yield and fruit quality are two major drivers of input allocation and, ultimately, revenue for grape producers. Because yield and fruit quality vary substantially from year-to-year and within a single block, opportunities exist for optimization via precision management activities that could lead to more profitable and sustainable grape production. Here, we review recent advances in the techniques and technology used to measure, estimate, and forecast grapevine yield and fruit quality. First, we discuss direct “measurement” of yield and quality (i.e. ground-truth data generation), with an emphasis on potential for scalability and automation. Second, we discuss technology and techniques that do not directly measure yield and quality, but use correlated measurements for their estimation.

Climate influence on grapevine physiology is prevalent and this influence is only expected to increase with climate change. Although governed by a general determinism, climate influence on grapevine physiology may present variations according to the terroir. In addition, these site-specific differences are likely to be enhanced when climate influence is studied using farm data. Indeed, farm data integrate additional sources of variation such as a varying representativity of the conditions actually experienced in the field. Nevertheless, there is a real challenge in valuing farm data to enable grape growers to understand their own terroir and consequently adapt their practices to the local conditions. In such a context, this article proposes a framework to site-specifically study climate influence on grapevine physiology using farm data. It focuses on improving the analysis of time series of weather data. The analytical framework includes the synchronization of time series using site-specific thermal indices computed with an original method called Extended Growing Degree Days (eGDD). Synchronized time series are then analyzed using a Bayesian functional Linear regression with Sparse Steps functions (BLiSS) in order to detect site-specific periods of strong climate influence on yield development. The article focuses on temperature and rain influence on grape yield development as a case study. It uses data from three commercial vineyards respectively situated in the Bordeaux region (France), California (USA) and Israel. For all vineyards, common periods of climate influence on yield development were found. They corresponded to already known periods, for example around veraison of the year before harvest. However, the periods differed in their precise timing (e.g. before, around or after veraison), duration and correlation direction with yield. Other periods were found for only one or two vineyards and/or were not referred to in literature, for example during the winter before harvest.