Defining the terroir of the Columbia gorge wine region, Oregon and Washington, USA using geographic information systems (GIS)

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.

Aim: Pests have a high impact on yield and grape quality in viticulture. An objective and rapid detection of pests under field conditions is needed. New sensing technologies and artificial intelligence could be used for pests detection in digital viticulture. The aim of this work was to apply computer vision and deep learning techniques for automatic detection of spider mite symptoms in grapevine under field conditions. 

Dans le vignoble champenois, le risque thermique associé au gel des bourgeons au printemps et en hiver est très mal connu et ne peut être envisagé qu’à l’échelle locale, en raison d’une variabilité spatiale forte. L’objectif de l’étude est d’appréhender ce risque de façon fiable et pluri locale en utilisant le réseau de stations météos récemment implanté.

Climate projections considered here are for two periods in the future throughout two IPCC scenarios: 2001 – 2030 (A1B) and 2071 – 2100 (A2) obtained using Coupled Regional Climate

L’Oltrepò Pavese est une zone de collines de la Lombardie, région située au nord de l’Italie avec un vignoble qui s’étend sur près de 15 000 ha. Cette zone représente la plus grande aire de production de la région et une des A.O.C. les plus étendues de tout le pays. Les cépages les plus cultivés, même historiquement, sont autochtones : la Barbera et la Croatina utilisés pour la production de vin rouge «Oltrepò» et le Pinot noir pour la production de vins mousseux. Pour le zonage viticole de cette A.O.C., il a été pris en considération: le climat, les sols, les caractéristiques viti-vinicoles.