Effects of stress memory on grapevine resilience in response to recurrent drought and recovery events 

After Champagne popping, the first consumer’s observation is the shape of the cork stopper. Consumers expect a “mushroom shape”. Nevertheless, we sometimes observe a “barrel” shape due to inappropriate cork’s elastic properties. The aim of this study was to follow the loss of cork stopper resiliency during 26 months according to the density (d) of the cork in contact with the wine. 1680 disks were weighed + measured and divided in 6 density classes: High (H1 d= 0,19 g/cm3 – H2 d= 0,21 g/cm3), Medium (M, not studied) and Low (L1 d= 0,13 g/cm3 – L2 d= 0,14 g/cm3). Then, 138 technical cork stoppers were produced for each of the 4 studied groups. These corks consisted of an agglomerated natural cork granule body to which two natural cork disks were glued. A total of 552 bottles of sparkling wine were closed with these corks and open after 13, 19 and 26 months to follow cork resiliencies. Wine bottles were stored horizontally; thus, the external natural cork disks were in contact to the wine. During the 26 months of the study, highly significant differences (ANOVA) were observed between the resiliencies of H-corks and those of L-corks, whatever the time studied. The diameters of the L-corks were statistically higher than those of the H-corks. No significant differences were observed between L1 and L2 corks. At the opposite, differences were noted between H1 and H2 at 19 and 26 months. This could be explained by the heterogeneity of the resiliency that was higher for H-corks than for L-corks. Finally, the corks were visually (12 judges) divided in 3 classes corresponding to high (expected mushroom shape, i.e high resiliency), medium (irregular shape of the disk in contact with the wine and/or low premature deterioration of the expected resiliency) and low qualities (barrel shape = premature deterioration of the resiliency). The corks were also divided in 3 categories corresponding to 0-33%, 34-66% and 67-100% resiliency. A strong correlation was noted between the visual and the instrumental categorizations. This study strongly evidenced 1) the importance of the cork density on the cork stopper behaviour when opening the bottle and 2) the interest of an instrumental approach reflecting the consumer’s perception.

Winemaking generates a significant amount of waste. Grape marc, the main solid residue, constitutes 20-25% of the pressed grapes and approximately 8-9 million tons are produced globally each year.

With 0.3 to 0.7 kg CO2eq per 0.75 L wine, the glass bottle is the main contributor to the carbon footprint of a bottle of wine.

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.

Drought is one of the main challenges for viticulture in the context of climate change. Selecting drought-tolerant plant material can be an effective strategy for a sustainable viticulture.