Un exemple de valorisation d’une étude de terroir au sein d’une unité coopérative de production à Saint Hilaire d’Ozilhan (Gard) dans les cotes du Rhône

The ripening of grapevine berries encompasses complex morphological and physiological processes, especially at veraison. Berry shrivel (BS) is a ripening physiological disorder affecting grape berries with visible symptoms appearing short after veraison. The main symptoms of BS are a strong reduction in sugar accumulation, inhibited anthocyanin biosynthesis and high pH values. The most popular red grape cultivar in Austria “Blauer Zweigelt” (Vitis vinifera L.) is specifically prone to develop the BS ripening disorder and up to date a no specific cause or causes could be identified. Recently omics approaches have identified and characterized key processes during grapevine ripening. Among them a small subset of genes, called SWITCH, have been described as markers for the onset of the ripening process in fruits.

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.

Berry composition at ripeness can be explained by many factors. This study was carried out from 2004 through 2011 in a 60 block network in the Yonne region, Burgundy.

While SO2 is one of the oldest and widest additive used in enology for its well-known antioxidant, anti-laccase and antimicrobial properties, it can cause health problems in some individuals.

The “Geoviticulture Multicriteria Climatic Classification (MCC) System” was developed to characterize the climate of the wine producing regions of the world.