About long time and vine quality modelisation e pistemological appro ach to geographical viticulture

Sauvignon blanc is characterized by distinctive aromas, both fruity and herbaceous. The “green” character has been attributed to the methoxypyrazines, while the “fruity” character is associated with polyfunctional mercaptans . Polyfunctional mercaptans are of great significance due to their high impact on wines and associated low perception thresholds. Elemental sulfur (S⁰) is widely used to protect grapevines from powdery mildew.

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.

One of the main sensory characteristics of red wine is astringency, which can be defined as drying, puckering and roughing of the oral cavity after the exposure to tannin-rich wines. Tannins are the main responsible for the intensity of the sensation as well for the qualitative aspects of astringency. However, the total intensity of the sensation is not sufficient to fully characterize red wine astringency. Thirty-three different subqualities (Gawel et al. 2001) had been generated to describe the complexity of this multi perceptual phenomenon, which includes both tastes, tactile, and flavor sensations. So, how to feel tannins during tasting? In this study, we used a sensory method that combine the training for astringency subqualities with touch-standards and the CATA questions, usually applied in consumer science, to evaluate the astringency subqualities of different typologies of Sangiovese: commercial and experimental wines. Sangiovese wine represents a good model for the study of astringency because it is generally characterized by a high content of low and high molecular weight proantocyanidins. Commercial wines differed for percentage of Sangiovese (80-100 %) grapes used in winemaking and for designation (Toscana TS, Chianti Classico CH, Chianti Riserva CR, Morellino di Scansano MS). The astringency profile of wines changed as the percentage of Sangiovese increased. Positive subqualities as velvet, soft, mouthcoat, and rich highly characterized the Sangiovese wine belonging to TS and CR designations. Moreover, the astringency subqualities related to blending or wood aging, represented the drivers of quality of commercial Sangiovese wines.

Many farming operations aim at controlling the leaf area of the vine according to its load. There are several techniques, direct and indirect, of estimate of this leaf area in a specific way, but impossible to implement at great scales. These last years, research in airborne and satellite remote sensing made it possible to show that a multispectral index of vegetation, computed from measurements of reflectances (red and near infrared), the « Normalised Difference Vegetation Index » (NDVI), is well correlated to the « Leaf Area Index » (leaf area per unit of ground) of the vine. Nevertheless these methods of acquisition and processing data are rather constraining and complex.

Climate change leads to even more hostile and stressful for the wine microorganism conditions and consequently issues with fermentation rate progression and off-character formation are frequently observed. The objective of the current research was to classify a great collection of yeast isolates from Greek wines based on their technological properties with oenological interest. Towards this direction, fourteen spontaneously fermented wines from different regions of Greece were collected for further yeast typing. The yeast isolates were subjected in molecular analyses and identification at species level.