Bees, climate changes, and “environmental sustainability 4.1c” in viticulture and the territory for a new global multiproductive “biometaethical district 4.1c”

The gradual change in rainfall patterns experienced in the south of France vineyards, especially around the Mediterranean sea, means that the vines are increasingly subject to summer drought. The winegrowers developped the use of irrigation techniques to ensure the maintenance of competitive yields in the production of wines under Protected Geographical Indication label. In practice, drip irrigation pipes can be installed above the ground or buried into the soil as well as at different distances from the vine row. The objective of this study was to examine the profiles of the wet bulbs of the soil obtained from two drip irrigation systems : aerial drip located under the vine row and subsurface drip placed in the middle of the inter-row. This experiment took place over two consecutive seasons (2020-2021) on a 3.4 ha Viognier plot in the Mediterranean region (PGI Oc, France) on sandy clay soil. The annual rainfalls were less than 400 mm. Soil water content probes were installed at different depths (20 – 40 – 60 – 80 cm) and at different lateralities from the vine row (30 – 60 – 90 – 120 cm) to control the formation of the soil wet bulb during irrigation. The mapping and the analysis of the data allowed a better understanding and differentiation of the water percolation when irrigating with subsurface or aerial drip. For the same amount of water and without differences of vine water status, it is shown that in a subsurface drip irrigation situation, the size of the wet bulb formed is larger than in aerial drip irrigation system.

“Flavescence dorée” (FD) is a grapevine quarantine disease associated with phytoplasmas and transmitted to healthy plants by insect vectors, mainly Scaphoideus titanus. Infected plants usually develop symptoms of stunted growth, unripe cane wood, leaf rolling, leaf yellowing or reddening, and shrivelled berries. Since plants can remain symptomless up to four years, they may act as reservoirs of FD contributing to the spread of the disease. So far, conventional management strategies rely mainly on the insecticide treatments, uprooting of infected plants and use of phytoplasma-free propagation material. However, these strategies are costly and could have undesirable environmental impacts. Thus, the development of sustainable and noninvasive approaches for early detection of FD and its management are of great importance to reduce disease spread and select the best cultural practices and treatments. The present study aimed to evaluate if multispectral/hyperspectral technologies can be used to detect FD before the appearance of the first symptoms and if infected grapevines display a spectral imaging fingerprint. To that end, physiological parameters (leaf area, chlorophyll content and photosynthetic rate) were collected in concomitance to the measurements of plant reflectance (using both a portable apparatus and a remote sensing drone). Measurements were performed in two leaves of 8 healthy and 8 FD-infected grapevines, at four timepoints: before the development of disease symptoms (21st June); and after symptoms appearance (ii) at veraison (2nd August); at post-veraison (11th September); and at harvest (25th September). At all timepoints, FD infected plants revealed a significant decrease in the studied physiological parameters, with a positive correlation with drone imaging data and portable apparatus analyses. Moreover, spectra of either drone imaging and portable apparatus showed clear differences between healthy and FD-infected grapevines, validating multispectral/ hyperspectral technology as a potential tool for the early detection of FD or other grapevine-associated diseases.

Most European vineyards are managed under rainfed conditions, where seasonal water deficit has become increasingly important. The flowering-veraison phenophase represents an important period for vine response to water stress, which is seldomly thoroughly evaluated. Therefore, we aim to quantify the flowering-veraison water stress levels using Crop Water Stress Indicator (CWSI) over 1986–2015 for important European wine regions, and to assess the respective potential Yield Lose Rate (YLR). Additionally, we also investigate whether an advanced flowering-veraison phase may help alleviating the water stress with improved yield. A process-based grapevine model STICS is employed, which has been extensively calibrated for flowering and veraison stages using observed data at 38 locations with 10 different grapevine varieties. Subsequently, the model is being implemented at the regional level, considering site-specific calibration results and gridded climate and soil datasets. The findings suggest wine regions with stronger flowering-veraison CWSI tend to have higher potential YLR. However, contrasting patterns are found between wine regions in France-Germany-Luxembourg and Italy-Portugal-Spain. The former tends to have slight-to-moderate drought conditions (CWSI<0.5) and a negligible-to-moderate YLR (<30%), whereas the latter possesses severe-to-extreme CWSI (>0.5) and substantial YLR (>40%). Wine regions prone to a high drought risk (CWSI>0.75) are also identified, which are concentrated in southern Mediterranean Europe. An advanced flowering-veraison phase may have benefited from cooler temperatures and a higher fraction of spring precipitation in wine regions of Italy-Portugal-Spain, resulting in alleviated CWSI and moderate reductions of YLR. For those of France-Germany-Luxembourg, this can have reduced flowering-veraison precipitation, but prevalent alleviations of YLR are also found, possibly because of shifted phase towards a cooler growing season with reduced evaporative demands. Overall, such a retrospective analysis might provide new insights towards better management of seasonal water deficit for conventionally vulnerable Mediterranean wine regions, but also for relatively cooler and wetter Central European regions.

Currently, the main goal of agriculture is to promote the resilience of agricultural systems in a sustainable way through the improvement of use efficiency of farm resources, increasing crop yield and quality under climate change conditions. This last is expected to drastically modify plant growth, with possible negative effects, especially in arid and semi-arid regions of Europe on the viticultural sector. In this context, the monitoring of spatial behavior of grapevine during the growing season represents an opportunity to improve the plant management, winegrowers’ incomes, and to preserve the environmental health, but it has additional costs for the farmer. Nowadays, UAS equipped with a VIS-NIR multispectral camera (blue, green, red, red-edge, and NIR) represents a good and relatively cheap solution to assess plant status spatial information (by means of a limited set of spectral vegetation indices), representing important support in precision agriculture management during the growing season. While differences between UAS-based multispectral imagery and point-based spectroscopy are well discussed in the literature, their impact on plant status estimation by vegetation indices is not completely investigated in depth. The aim of this study was to assess the performance level of UAS-based multispectral (5 bands across 450-800nm spectral region with a spatial resolution of 5cm) imagery, reconstructed high-resolution satellite (Sentinel-2A) multispectral imagery (13 bands across 400-2500 nm with spatial resolution of <2 m) through Convolutional Neural Network (CNN) approach, and point-based field spectroscopy (collecting 600 wavelengths across 400-1000 nm spectral region with a surface footprint of 1-2 cm) in a plant status estimation application, and then, using Bayesian regularization artificial neural network for leaf chlorophyll content (LCC) and plant water status (LWP) prediction. The test site is a Greco vineyard of southern Italy, where detailed and precise records on soil and atmosphere systems, in-vivo plant monitoring of eco-physiological parameters have been conducted.

Climate change challenges differently wine growing systems, depending on their biophysical, sociological and economic features. Therefore, there is a need to locally design and evaluate adaptation strategies combining several technical options, and considering the local opportunities and constraints (e.g. water access, wine typicity). The case study took place in a typical and heterogeneous Mediterranean vineyard of 1,500 ha in the South of France. We developed a participatory modeling approach to (1) conceptualize local climate change issues and design spatially explicit adaptation strategies with stakeholders, (2) numerically evaluate their effects on phenology, yield and irrigation needs under the high-emissions climate change scenario RCP 8.5, and (3) collectively discuss simulation results. We organized five sets of workshops, with in-between modeling phases. A process-based model was developed that allowed to evaluate the effects of six technical options (late varieties, irrigation, water saving by reducing canopy size, adjusting cover cropping, reducing density, and shading) with various distributions in the watershed, as well as vineyard relocation. Overall, we co-designed three adaptation strategies. Delay harvest strategy with late varieties showed little effects on decreasing air temperature during ripening. Water constraint limitation strategy would compensate for production losses if disruptive adaptations (e.g. reduced density) were adopted, and more land got access to irrigation. Relocation strategy would foster high premium wine production in the constrained mountainous areas where grapevine is less impacted by climate change. This research shows that a spatial distribution of technical changes gives room for adaptation to climate change, and that the collaboration with local stakeholders is a key to the identification of relevant adaptation. Further research should explore the potential of adaptation strategies based on soil quality improvement and on water stress tolerant varieties.