Application of GiESCO “bio-metaethics” charter in practice: the “direct” involvement of vine grower, winemaker, society

Terroir is not only a geographical site, but it is a more complex concept able to express the “collective knowledge of the interactions” between the environment and the vines mediated through human action and “providing distinctive characteristics” to the final product (OIV 2010). It is often treated and accepted as a “black box”, in which the relationships between wine and its origin have not been clearly explained. Nevertheless, it is well known that terroir expression is strongly dependent on the physical environment, and in particular on the interaction between soil-plant and atmosphere system, which influences the grapevine responses, grapes composition and wine quality. The Terroir studying and mapping are based on viticultural zoning procedures, obtained with different levels of know-how, at different spatial and temporal scales, empiricism and complexity in the description of involved bio-physical processes, and integrating or not the multidisciplinary nature of the terroir. The scientific understanding of the mechanisms ruling both the vineyard variability and the quality of grapes is one of the most important scientific focuses of terroir research. In fact, this know-how is crucial for supporting the analysis of climate change impacts on terroir resilience, identifying new promised lands for viticulture, and driving vineyard management toward a target oenological goal. In this contribution, an overview of the last findings in terroir studies and approaches will be shown with special attention to the terroir resilience analysis to climate change, facing the use and abuse of terroir concept and new technology able to support it and identifying the terroir zones.

The main innovation in the VINIoT service is the joint use of two technologies that are currently used separately: vineyard monitoring using multispectral imaging and deployed terrain sensors. One part of the system is based on the development of artificial intelligence algorithms that are feed on the images of the multispectral camera and IoT sensors, high-level information on water stress, grape ripening status and the presence of diseases. In order to obtain algorithms to determine the state of ripening of the grapes and avoid losing information due to the diversity of the grape berries, it was decided to work along the first year 2020 at berry scale in the laboratory, during the second year at the cluster scale and on the last year at plot scale. Different varieties of white and red grapes were used; in the case of Galicia we worked with the white grape variety Treixadura and the red variety Mencía. During the 2020 and 2021 campaigns, multispectral images were taken in the visible and infrared range of: 1) sets of 100 grapes classifying them by means of densimetric baths, 2) individual bunches. The images taken with the laboratory analysis of the ripening stage were correlated. Technological maturity, pH, probable degree, malic acid content, tartaric acid content and parameters for assessing phenolic maturity, IPT, anthocyanin content were determined. It has been calculated for each single image the mean value of each spectral band (only taking into account the pixels of interest) and a correlation study of these values with laboratory data has been carried out. These studies are still provisional and it will be necessary to continue with them, jointly with the training of the machine learning algorithms. Processed data will allow to determine the sensitivity of the multispectral images and select bands of interest in maturation.

“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.

Late spring frost is a major challenge for various winegrowing regions across the world, its occurrence often leading to important yield losses and/or plant failure. Despite a significant increase in minimum temperatures worldwide, the spatial and temporal evolution of spring frost risk under a warmer climate remains largely uncertain. Recent projections of spring frost risk for viticulture in Europe throughout the 21st century show that its evolution strongly depends on the model approach used to simulate budburst. Furthermore, the frost damage modelling methods used in these projections are usually not assessed through comparison to field observations and/or frost damage reports.
The present study aims at comparing frost risk projections simulated using six spring frost models based on two approaches: a) models considering a fixed damage threshold after the predicted budburst date (e.g BRIN, Smoothed-Utah, Growing Degree Days, Fenovitis) and b) models considering a dynamic frost sensitivity threshold based on the predicted grapevine winter/spring dehardening process (e.g. Ferguson model). The capability of each model to simulate an actual frost event for the Vitis vinifera cv. Chadonnay B was previously assessed by comparing simulated cold thermal stress to reports of events with frost damage in Chablis, the northernmost winegrowing region of Burgundy. Models exhibited scores of κ > 0.65 when reproducing the frost/non-frost damage years and an accuracy ranging from 0.82 to 0.90.
Spring frost risk projections throughout the 21st century were performed for all winegrowing subregions of Bourgogne-Franche-Comté under two CMIP5 concentration pathways (4.5 and 8.5) using statistically downscaled 8×8 km daily air temperature and humidity of 13 climate models. Contrasting results with region-specific spring frost risk trends were observed. Three out of five models show a decrease in the frequency of frost years across the whole study area while the other two show an increase that is more or less pronounced depending on winegrowing subregion. Our findings indicate that the lack of accuracy in grapevine budburst and dehardening models makes climate projections of spring frost risk highly uncertain for grapevine cultivation regions.

There is an urgent need in viticulture to adopt alternative herbicide-free soil management strategies to mitigate climate change, increase biodiversity, reduce plant protection products and improve soil quality while minimizing detrimental effects on grapevine’s stress tolerance and fruit quality. To propose sustainable solutions, adapted to different pedoclimatic conditions in Switzerland, we developed a multidisciplinary 4-year project, started in 2020. Objectives of the project are to a) evaluate the impact of green covers (spontaneous flora, winter cover crop and permanent ground cover) on environmental and agronomic parameters and b) develop subsequently innovative strategies for different viticultural contexts of Switzerland. The project is divided into 3 phases: 1) diagnosis, 2) on-farm and 3) on-station experiments. Phase 1) consisted in an assessment of 30 commercial vineyards all over Switzerland, where growers already use different herbicide-free soil management strategies. The most promising practices identified in this exploratory phase will be replicated in commercial vineyards across Switzerland (“on-farm”) as well as in a classical randomized block design in an experimental plot (“on-station”). For phase 1), measurements consisted in evaluation of soil status (compaction, structure, roots development), soil microbial diversity (metagenomics), plant diversity and biomass, vine physiology (water stress, vigor, leaf nitrogen) and berry quality (acidity, sugar, available nitrogen). Interestingly, the permanent ground cover resulted in a higher Shannon index thus a higher biodiversity as compared to the other itineraries. The winter cover crop increased vine nitrogen and vigor while deteriorating soil quality, leaving the soil more exposed and compacted likely due to more frequent tillage. The spontaneous flora led to higher berry sugar accumulation, less nitrogen and higher malic acid concentration putatively due to a higher water retention of the flora in a particularly wet vintage. Phases 2) and 3) are required to confirm those tendencies, over the 3 next vintages and different climatic conditions.