L’Appellation d’Origine Contrôlée « Huile Essentielle de Lavande de Haute Provence »

The maturation patterns process has been very studied. In particular the modelization of the sugars and titratable acidity during the ripening period was an important approach, in particular for the prediction of harvest date (Barillere et al., 1988; Jourion et al.,1987; Maujean et al., 1983; Scienza, 1989). In Oltrepò Pavese, the widest viticultural district of Lombardy – Northern Italy – (about 15000 hectares), grape maturation trends shows high variability, due to the large variation in environmental characteristics of vineyards (altitude, exposure, soil type, mesoclimate) and to “cultivar x environment” interaction.

Global climate change affects regional climates and hold implications for wine growing regions worldwide. Although winegrowers are constantly adapting to internal and external factors, it seems relevant to develop tools, which will allow them to better define actual and future agro-climatic potentials. Within this context, we develop a modelling approach, able to simulate the impact of environmental conditions and constraints on vine behaviour and to highlight potential adaptation strategies according to different climate change scenarios. Our modeling approach, named SEVE (Simulating Environmental impacts on Viticultural Ecosystems), provides a generic modeling framework for simulating grapevine growth and berry ripening under different conditions and constraints (slope, aspect, soil type, climate variability…) as well as production strategies and adaptation rules according to climate change scenarios. Each activity is represented by an autonomous agent able to react and adapt its reaction to the variability of environmental constraints. Using this model, we have recently analyzed the evolution of vineyards’ exposure to climatic risks (frost, pathogen risk, heat wave) and the adaptation strategies potentially implemented by the winegrowers. This approach, implemented for two climate change scenarios, has been initiated in France on traditional (Loire Valley) and emerging (Brittany) vineyards. The objective is to identify the time horizons of adaptations and new opportunities in these two regions. Carried out in collaboration with wine growers, this approach aims to better understand the variability of climate change impacts at local scale in the medium and long term.

Acidity adjustments are key to microbial control, sensory quality and wine longevity. Acidification with cation exchange resins -in acid cycle- offers the possibility to reduce the pH by exchanging wine cations, such as potassium (K+), for hydrogen ions (H+). During the exchange process, the removal of potassium and calcium ions contributes to limiting the formation of tartrate salts, thus offering an alternative solution to conventional methods for tartrate stability. Moreover, the reduction of wine pH and the removal of metals catalyzers (e.g. iron) could positively impact the wine’s oxidative stability. Therefore, the aims of this work were (a) to optimize the ion exchange process by testing different volumes and concentrations of sulfuric acid (H2SO4) during the acid cycle, (b) evaluate the effects of the ion exchange process on the formation of tartrate salts, and (c) analyze the oxidative stability of the treated wines.

The hill Somló looks like a huge island wich jumps out of the see, a few kilometers away from the slope of Bakony highland and on the edge of the Hungarian small plane.

Drought and heat waves deriving from climate change have been affecting grapevine plants and altering wine characteristics in the past years, and effects are expected to get worst. Innovative approaches to address this problem have been undertaken in several varieties, that consist in exploring intravarietal variability to identify genotypes that are tolerant to abiotic stress. Such is the case of the variety Arinto, where an experimental population of 165 clones installed according to a resolvable row-column design with 6 replicates, was scanned for several parameters, including surface leaf temperature (SLT). Linear mixed models were fitted to the data of the traits evaluated, and the empirical best linear unbiased predictors (EBLUPs) of genotypic effects for each trait were obtained as well as the coefficient of genotypic variation (CVG) and broad sense heritability.