Mechanisms involved in the heating of the environment by the aerodynamic action of a wind machine to protect a vineyard against spring frost

One of the major issues for the wine sector is the impact of climate change linked to the increasing temperatures which affects physicochemical parameters of the grape varieties planted in Bordeaux vineyard and consequently, the quality of wine. In some varietals, the attenuation of their fresh fruity character is accompanied by the accentuation of dried-fruit notes [1]. As a new adaptive strategy on climate change, some winegrowers have initiated changes in the Bordeaux blend of vine varieties [2]. This study intends to explore the fruitiness in wines produced from grape varieties adapted to the future climate of Bordeaux. 10 commercial single–varietal wines from 2018 vintage made from the main grape varieties in the Bordeaux region (Cabernet franc, Cabernet-Sauvignon and Merlot) as well as from indigenous grape varieties from the Mediterranean basin, such as Cyprus (Yiannoudin), France (Syrah), Greece (Agiorgitiko and Xinomavro), Portugal (Touriga Nacional) and Spain (Garnacha and Tempranillo), were selected among 19 samples using sensory descriptive analyses. Both sensory and instrumental analyses were coupled, to investigate their fruity aroma expression. For sensory analysis, samples were prepared from wine, using a semi preparative HPLC method which preserves wine aroma and isolates fruity characteristics in 25 specific fractions [3,4]. Fractions of interest with intense fruity aromas were sensorially selected for each wine by a trained panel and mixed with ethanol and microfiltered water to obtain fruity aromatic reconstitutions (FAR) [5]. A free sorting task was applied to categorize FAR according to their similarities or dissimilarities, and different clusters were highlighted. Instrumental analysis of the different FAR and wines demonstrated variations in their molecular composition. Results obtained from sensory and gas chromatography analysis enrich the knowledge of the fruity expression of red wines from “new” grape varieties opening up new perspectives in wine technology, including blending, thus providing new tools for producers.

New and developing technologies, that provide sensors and the software systems for using and interpreting them, are becoming pervasive through our lives and society. From smart phones to cars to farm machinery, all contain a range of sensors that are monitored automatically with intelligent software, providing us with the information we need, when we need it. This technological revolution has the potential to monitor all aspects of vineyard activity, assisting growers to make the management choices they need to achieve the outcomes they want. For example, a future vineyard may possess automated imaging that generates a three dimensional model of the vine canopy, highlighting differences from the desired structure and how to use canopy management to improve fruit composition, or generates maps with yield estimates and measurements of berry composition throughout the growing season.

Agri-photovoltaics (apv) describes the dual use of an agricultural area for food production and solar power generation. There are already a number of systems in operation around the world with various crops and under a wide range of different set-ups. In large parts, they still allow mechanical cultivation and other positive side effects of an APV system were observed in addition to the increase in utilization in the form of electricity and food: effects on the water balance and passive protection against extreme weather events.

During wine storage and aging, microorganisms capable of degrading malic acid in an undesirable manner can proliferate.

Aim: Downy mildew is a crucial disease in viticulture. In-field evaluation of downy mildew has been classically based on visual inspection of leaves and fruit. Nevertheless, non-invasive sensing technologies could be used for disease detection in grapevine. The aim of this study was to assess downy mildew severity in grapevine leaves using machine vision.