Everything else, it’s work ”Socio-cultural dimensions of terroir among Bordeaux winemakers

Excessive fertilization of the vineyard leads to low quality grapes, increased costs and a negative impact on the environment. In order to establish an integrated management system aimed at a sustainable fertilization of the vineyards, nutritional reference levels were established. For this purpose, 30 representative vineyards of the Albariño variety were studied, in which soil and petiole analyses were carried out for two years and grape yield and quality at harvest were measured. In both years of study, soil pH, calcium, sodium and cation exchange capacity were positively correlated with calcium content and negatively correlated with manganese in grapes. Irrigated vineyards had higher levels of aluminium in soil and lower levels of calcium in petiole. Climatic conditions were very different in the years of the study. The year 2019 was colder than usual, in 2020 there was a marked water stress with high summer temperatures. This resulted in medium-high acidity in grapes in 2019 and low acidity in 2020, with sugar levels being similar both years. A very marked decrease in must amino nitrogen was observed in 2020, with ammonia nitrogen remaining stable. The correlation of acidity and sugar values in grapes with soil and petiole analysis data made it possible to establish reference levels for the nutritional diagnosis of the Albariño variety in this region. Based on these results, an easy-to-use TIC application is currently being created for grapegrowers, aimed at improving the sustainability of the vineyard through reasoned fertilization. This study has now been extended to other Galician vine varieties.

With the aim of producing premium wines, it is admitted that moderate environmental stresses may contribute to the accumulation of compounds of interest in grapes. However the ongoing climate change, with the appearance of more limiting conditions of production is a major concern for the wine industry economic. Will it be possible to maintain the vineyards in place, to preserve the current grape varieties and how should we anticipate the adaptation measures to ensure the sustainability of vineyards? In this context, the question of the responses and adaptation of grapevine to abiotic stresses becomes a major scientific issue to tackle. An abiotic stress can be defined as the effect of a specific factor of the physico-chemical environment of the plants (temperature, availability of water and minerals, light, etc.) which reduces growth, and for a crop such as the vine, the yield, the composition of the fruits and the sustainability of the plants. Water stress is in many minds, but a systemic vision is essential for at least two reasons. The first reason is that in natural environments, a single factor is rarely limiting, and plants have to deal with a combination of constraints, as for example heat and drought, both in time and at a given time. The second reason is that plants, including grapevine, have central mechanisms of stress responses, as redox regulatory pathways, that play an important role in adaptation and survival. Here we will review the most recent studies dealing with this issue to provide a better understanding of the grapevine responses to a combination of environmental constraints and of the underlying regulatory pathways, which may be very helpful to design more adapted solutions to cope with climate change.

Understanding vineyard variability to target management strategies, apply inputs efficiently and deliver consistent grape quality to the winery is essential. However, despite inherent vineyard variability, the majority are managed as if they are uniform. VitiCanopy is a simple, grower-friendly tool for precision/digital viticulture that allows users to collect and interpret objective spatial information about vineyard performance. After four years of field and market research, an upgraded VitiCanopy has been created to achieve a more streamlined, technology-assisted vine monitoring tool that provides users with a set of superior new features, which could significantly improve the way users monitor their grapevines. These new features include:
• New user interface
• User authentication
• Batch analysis of multiple images
• Ease the learning curve through enhanced help features
• Reporting via the creation of colour maps that will allow users to assess the spatial differences in canopies within a vineyard.
Use-case examples are presented to demonstrate the quantification and mapping of vineyard variability through objective canopy measurements, ground-truthing of remotely sensed measurements, monitoring of crop conditions, implementation of disease and water management decisions as well as creating a history of each site to forecast quality. This intelligent tool allows users to manage grapevines and make informed management choices to achieve the desired production targets and remain profitable.

Stomatal traits determine grapevine water use, carbon supply, and water stress, which directly impact yield and berry chemistry. Breeding for stomatal traits has the strong potential to improve grapevine performance under future, drier conditions, but the trait values that breeders should target are unknown. We used a functional-structural plant model developed for grapevine (HydroShoot) to determine how stomatal traits impact canopy gas exchange, water potential, and temperature under historical and future conditions in high-quality and hot-climate California wine regions (Napa and the Central Valley). Historical climate (1990-2010) was collected from weather stations and future climate (2079-99) was projected from 4 representative climate models for California, assuming medium- and high-emissions (RCP 4.5 and 8.5). Five trait parameterizations, representing mean and extreme values for the maximum stomatal conductance (gmax) and leaf water potential threshold for stomatal closure (Ψsc), were defined from meta-analyses. Compared to mean trait values, the water-spending extremes (highest gmax or most negative Ysc) had negligible benefits for carbon gain and canopy cooling, but exacerbated vine water use and stress, for both sites and climate scenarios. These traits increased cumulative transpiration by 8 – 17%, changed cumulative carbon gain by -4 – 3%, and reduced minimum water potentials by 10 – 18%. Conversely, the water-saving extremes (lowest gmax or least negative Ψsc) strongly reduced water use and stress, but potentially compromised the carbon supply for ripening. Under RCP 8.5 conditions, these traits reduced transpiration by 22 – 35% and carbon gain by 9 – 16% and increased minimum water potentials by 20 – 28%, compared to mean values. Overall, selecting for more water-saving stomatal traits could improve water-use efficiency and avoid the detrimental effects of highly negative canopy water potentials on yield and quality, but more work is needed to evaluate whether these benefits outweigh the consequences of minor declines in carbon gain for fruit production.

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.