Optimizing disease management in the Rioja wine region: a study on Erisiphe necator and the Gubler-Thomas model

Must oxidation is a complex process involving multiple enzymatic transformations, including the oxidation of phenolics containing an ortho-diphenol function. The latter process has a primary influence on wine aroma characteristics and stability, due to the central role of ortho-diphenols in the non-enzymatic oxidative reactions taking place during winemaking and in finished wine. Although oxidation of must is traditionally avoided, in recent years its contribution to wine quality has been revisited, and in some cases improvements to wine aroma have been observed with the application of controlled must oxidation. Nowadays there is a great interest in the wine industry towards the identification of specific markers or patterns to characterize and classify the response of grape must to oxidation.

In a context of climate change and excessive use of agrochemical products, sustainable approaches for environmental and human health such as the use of bio stimulants in viticulture represent a potential option, against abiotic and biotic threats. Bio stimulants are organic compounds, microbes, or a combination of both, that stimulate plant’s vital processes, allowing high yields and good quality products. In vines, may trigger an innate immune response leading to the synthesis of secondary metabolites, key compounds for the organoleptic properties of grapes and wines.

The impact of viticulture on soil can be determined by comparing the biophysical properties that represent soil health at a particular site and depth with those same properties in soil considered to represent the ‘pre-vineyard’ state (the headland). Information gathered by this method shows the changes in soil properties following the change to viticulture depend on individual vineyard management and environment.

In viticulture, a warming climate can have a very significant impact on grapevine development and therefore on the quality and characteristics of wines across different spatial scales, ranging from global to local. In order to adapt wine-growing to climate change, global climate models can be used to define future scenarios, but only at the scale of major wine regions. Despite the huge progress made over the last ten years in terms of the spatial resolution of climate models (now downscaled to a few square kilometres), they are not yet sufficiently precise to account for the local climate variability associated with such parameters as local topography, in spite of these parameters being decisive for vine and wine characteristics. This study describes a method to downscale future climate scenarios to vineyard scale. Networks of data loggers have been used to collect air temperature at canopy level in the Waipara winegrowing region (New Zealand) over five growing seasons. These measurements allow the creation of fine-scale geostatistical models and maps of temperature (at 100 m resolution) for the growing season. In order to model climate change at pilot site scale, these geostatistical models have been combined with regional climate change predictions for the periods 2031-2050 and 2081-2100 based on the RCP8.5 climate change scenario. The integration of local climate variability with regionalized climate change simulations allows assessment of the impacts of climate change at the vineyard scale. The improved knowledge gained using this methodology results from the increased horizontal resolution that better addresses the concerns of winegrowers. The results provide the local winegrowers with information necessary to understand current processes, as well as historical and future viticulture trends at the scale of their site, thereby facilitating decisions about future response strategies.

Cet article propose la formalisation d’un modèle paramétrique pour représenter l’accumulation des sucres dans les baies de raisin durant la maturation. Le test de ce modèle sur des jeux de données réels a permis de valider l’approche proposée. Une seconde partie est axée sur l’adaptation de la méthode pour permettre la simulation du comportement du millésime en cours dès les premiers relevés de maturité. Ce travail possède de multiples applications dans le domaine de l’aide à la décision.