Un Système d’Informations à Références Spatiales sur le Vignoble. Un outil performant d’aide aux recherches sur la caractérisation des terroirs viticoles

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.

Heatwaves or extreme heat events can be particularly harmful to agriculture. Grapevines grown in the Douro winemaking region are particularly exposed to this threat, due to the specificities of the already warm and dry climatic conditions. Furthermore, climate change simulations point to an increase in the frequency of occurrence of these extreme heat events, therefore posing a major challenge to winegrowers in the Mediterranean type climates. The current study focuses on the application of the STICS crop model to assess the potential impacts of heatwaves in grapevine yields over the Douro valley winemaking region. For this purpose, STICS was applied to grapevines using high-resolution weather, soil and terrain datasets over the Douro. To assess the impact of heatwaves, the weather dataset (1989-2005) was artificially modified, generating periods with anomalously high temperatures (+5 ºC), at certain onset dates and with specific durations (from 5 to 9 days). The model was run with this modified weather dataset and results were compared to the original unmodified runs. The results show that heatwaves can have a very strong impact on grapevine yields, strongly depending on the onset dates and duration of the heatwaves. The highest negative impacts may result in a decrease in the yield by up to -35% in some regions. Despite some uncertainties inherent to the current modelling assessment, the present study highlights the negative impacts of heatwaves on viticultural yields in the Douro region, which is critical information for stakeholders within the winemaking sector for planning suitable adaptation measures.

As an essential element for grapevine development and yield, nitrogen is also involved in the winemaking process and largely affects wine composition. Grape must amino nitrogen deficiency affects the alcoholic fermentation kinetics and alters the development of wine aroma precursors. It is therefore essential to control and optimize nitrogen use efficiency by the plant to guarantee suitable grape nitrogen composition at harvest. Understanding the impact of environmental conditions and cultural practices on the plant nitrogen metabolism would allow us to better orientate our technical choices with the objective of quality and sustainability (less inputs, higher efficiency). This trial focuses on the impact of crop limitation – that is a common practice in European viticulture – on nitrogen distribution in the plant and particularly on grape nitrogen composition. A wide gradient of crop load was set up in a homogeneous plot of Chasselas (Vitis vinifera) in the experimental vineyard of Agroscope, Switzerland. Dry weight and nitrogen dynamics were monitored in the roots, trunk, canopy and grapes, during two consecutive years, using a 15N-labeling method. Grape amino nitrogen content was assessed in both years, at veraison and at harvest. The close relationship between fruits and roots in the maintenance of plant nitrogen balance was highlighted. Interestingly, grape nitrogen concentration remained unchanged regardless of crop load to the detriment of the growth and nitrogen content of the roots. Meanwhile, the size and the nitrogen concentration of the canopy were not affected. Leaf gas exchange rates were reduced in response to lower yield conditions, reducing carbon and nitrogen assimilation and increasing intrinsic water use efficiency. The must amino nitrogen profiles could be discriminated as a function of crop load. These findings demonstrate the impact of plant balance on grape nitrogen composition and contribute to the improvement of predictive models and sustainable cultural practices in perennial crops.

The Earth’s system is undergoing major changes through a wide range of spatial and temporal scales as a response to growing anthropogenic radiative forcing, which is pushing the whole system far beyond its natural variability. Sources of greenhouse gases largely exceed their sinks, thus leading to a strengthened greenhouse effect. More energy is thereby being supplied to the system, with inevitable shifts in climatic patterns and weather regimes. Over the last decades, these modifications have been manifested in the full statistical distributions of the atmospheric variables, with dramatic changes in the frequency and intensity of extremes. Natural hazards, such as severe droughts, floods, forest fires, or heatwaves, are being triggered by extreme atmospheric events worldwide, thus threatening human activities. Viticultculture is not only exposed to changing climates but is also highly vulnerable, as grapevine phenology and physiological development are strongly controlled by atmospheric conditions. Therefore, the assessment of climate change projections for a given region is critical for climate change adaptation and risk reduction in viticulture. By adopting timely and suitable measures, the future sustainability and resiliency of the sector can be fostered. Climate-grapevine chain modelling is an essential tool for better planning and management. However, the accuracy of the resulting projections is limited by many uncertainties that must be duly taken into account when transferring knowledge to stakeholders and decision-makers. Climate-smart viticulture will comprise ensembles of locally tuned strategies, envisioning both adaptation and mitigation, assisted by emerging technologies and decision-support systems.

The development of new generations of multispectral satellites such as Sentinel-2 opens possibilities as to vine water status assessment (Cohen et al., 2019). Based on a three years field campaign, a model of Stem Water Potential (SWP) estimation on vine using four satellite bands in Red, Red-Edge, NIR and SWIR domains was developed (Laroche-Pinel et al., 2021). The model relies on SWP field measures done using a pressure chamber (Scholander et al., 1965), which is a common, robust and precise method to assess vine water status (Acevedo-Opazo et al., 2008). The model was mainly developed from from SWP measures on Syrah N (Laroche Pinel E., 2021).

A large scale monitoring was organized in different vineyards in the Mediterranean region in 2021. 10 varieties amongst the most represented in this area were monitored (Cabernet sauvignon N, Chardonnay B, Cinsault N, Grenache N, Merlot N, Mourvèdre N, Sauvignon B, Syrah N, Vermentino B, Viognier B). The model was used to produce water status maps from Sentinel-2 images, starting from the beginning of June (fruit set) up to September (harvest). The average estimated SWP for each vine was compared to actual field SWP measures done by wine growers or technicians during usual monitoring of irrigation programs. The correlations between mean estimated SWP and mean measured SWP were at the same level than expected by the model. (Laroche Pinel, 2021) The general SWP kinetics were comparable. The estimated SWP would have led to same irrigation decisions concerning the date of first irrigation in comparison with measured SWP.

Acevedo-Opazo, C., Tisseyre, B., Ojeda, H., Ortega-Farias, S., Guillaume, S. (2008). Is it possible to assess the spatial variability of vine water status? OENO One, 42(4), 203.
Cohen, Y., Gogumalla, P., Bahat, I., Netzer, Y., Ben-Gal, A., Lenski, I., … Helman, D. (2019). Can time series of multispectral satellite images be used to estimate stem water potential in vineyards? In Precision agriculture ’19, The Netherlands: Wageningen Academic Publishers, pp. 445–451.
Laroche-Pinel, E., Duthoit, S., Albughdadi, M., Costard, A. D., Rousseau, J., Chéret, V., & Clenet, H. (2021). Towards vine water status monitoring on a large scale using sentinel-2 images. remote sensing, 13(9), 1837.
Laroche-Pinel,E. (2021). Suivi du statut hydrique de la vigne par télédétection hyper et multispectrale. Thèse INP Toulouse, France.
Scholander, P.F., Bradstreet, E.D., Hemmingsen, E.A., & Hammel, H.T. (1965). Sap pressure in vascular plants: Negative hydrostatic pressure can be measured in plants. Science, 148(3668), 339–346.