Diversity in grape composition for sugars and acidity opens options to mitigate the effect of warming during ripening

Grapevine interspecific hybrids (PIWIs, from German “pilzwiderstandsfähige Rebsorten” meaning fungus tolerant grapevine cultivars), offer a promising alternative to traditional cultivars in many wine regions due to their tolerance to certain fungal diseases. This makes them a potential solution for sustainable wine production, particularly under organic systems. Despite extensive research on certain agronomic traits and susceptibility to biotic diseases, such as powdery and downy mildews, the response of these cultivars to abiotic stressors, such as drought, remains unclear. Our study aims to investigate the eco-physiological traits of two commercial PIWI cultivars, Muscaris and Souvignier gris, at the leaf level to evaluate their response to drought stress.

Downy mildew, caused by Plasmopara viticola, is the most economically impactful disease affecting grapevines. This polycyclic pathogen triggers both primary and secondary infection cycles, resulting in significant yield losses when effective disease control measures are lacking. Over the winter, the pathogen survives by forming resting structures, the oospores, derived from sexual reproduction, which produce the inoculum for primary infections. To optimize grapevine downy mildew control and obtain the desired levels of production while minimizing chemical inputs, it is crucial to optimize the timeframe for fungicide application. Disease forecasting models are useful to identify the infection risk.

Oxidation processes constitute a main problem in winemaking. Oxidation result in color browning and varietal aroma loss, which are key attributes of wine organoleptic quality [1]. Despite the mechanisms involved in wine oxidation have been extensively reviewed [2], the protection of wine against oxidative spoilage remains one of the main goals of winemaking.
SO2 is one of the most efficient wine antioxidants used to prevent oxidation and microbial spoilage. However, intolerances caused by SO2 have led to the reduction of its concentration in wines.

Grapevine yield is a key indicator to assess the impacts of climate change and the relevance of adaptation strategies in a vineyard landscape. At this scale, a yield model should use a number of parameters and input data in relation to the information available and be able to reproduce vineyard management decisions (e.g. soil and canopy management, irrigation). In this study, we used data from six experimental sites in Southern France (cv. Syrah) to calibrate a model of grapevine yield limited by water constraint (GraY). Each yield component (bud fertility, number of berries per bunch, berry weight) was calculated as a function of the soil water availability simulated by the WaLIS water balance model at critical phenological phases. The model was then evaluated in 10 grapegrowers’ plots, covering a diversity of biophysical and technical contexts (soil type, canopy size, irrigation, cover crop). We identified three critical periods for yield formation: after flowering on the previous year for the number of bunches and berries, around pre-veraison and post-veraison of the same year for mean berry weight. Yields were simulated with a model efficiency (EF) of 0.62 (NRMSE = 0.28). Bud fertility and number of berries per bunch were more accurately simulated (EF = 0.90 and 0.77, NRMSE = 0.06 and 0.10, respectively) than berry weight (EF = -0.31, NRMSE = 0.17). Model efficiency on the on-farm plots reached 0.71 (NRMSE = 0.37) simulating yields from 1 to 8 kg/plant. The GraY model is an original model estimating grapevine yield evolution on the basis of water availability under future climatic conditions.  It allows to evaluate the effects of various adaptation levers such as planting density, cover crop management, fruit/leaf ratio, shading and irrigation, in various production contexts.

During the year 2009 we have studied the phenology and grape composition of Mencía cultivar in seven different situations (orientation and altitude) for Amandi subzone