Viticultural practices: past, present and future

Globalisation and climate change have radically transformed world wine production upsetting the established order of wine ecologies. Ecological risks and the future of traditional agricultural systems are widely debated in anthropology, but very little is understood of the particular challenges posed by climate change to viticulture which is seen by many as the canary in the coalmine of global agriculture. Moreover, wine as a globalised embedded commodity provides a particularly telling example for the study of climate change having already attracted early scientific attention. Studies of climate change in viticulture have focused primarily on the production of systematic models of adaptation and vulnerability, while the human and cultural factors, which are key to adaptation and sustainable futures, are largely missing. Climate experts have been unanimous in recognising the urgent need for a better understanding of the complex dynamics that shape how climate change is experienced and responded to by human systems. Yet this call has not yet been addressed. Climate ethnography, coined by the anthropologist Susan Crate (2011), aims to bridge this growing disjuncture between climate science and everyday life through the exploration of the social meaning of climate change. It seeks to investigate the confrontation of its social salience in different locations and under different environmental guises (Goodman 2018: 340). By understanding how wine producers make sense of the world (and the environment) and act in it, it proposes to focus on the co-production of interdisciplinary knowledge by identifying and foreshadowing problems (Goodman 2018: 342; Goodman & Marshall 2018). It seeks to offer an original, transformative and contrasted perspective to climate change scenarios by investigating human agency -individual or collective- in all its social, political and cultural diversity. An anthropological approach founded on detailed ethnographies of wine production is ideally placed to address economic, social and cultural disruptions caused by the emergence of these new environmental challenges. Indeed, the community of experts in environmental change have recently called for research that will encompass the human dimension and for more broad-based, integrated through interdisciplinarity, useful knowledge (Castree & al 2014). My paper seeks to engage with climate ethnography and discuss what it brings to the study of wine environmental futures while exploring the limitations of the anthropological environmental approach.

IFV, INRAe and the national network “Partenaires de la Sélection Vigne” representing 37 organizations from the different wine regions, have been working increasingly closely over the last 2 decades towards the preservation of the French varietal patrimony. There are approximately 600 patrimonial varieties according to INRAe and SupAgro Montpellier experts, including ancient cultivars (400) and intravarietal crossbreeds obtained since the 19th century. In the context of a drastic reduction in such varieties from the mid 1980’s in favor of mainstream varieties, it was essential to carry out an inventory of old vines and vineyards. INRAe Vassal collection plays a key role here as it holds the largest diversity available, along with a rich bibliography and herbariums, offering us the opportunity to document and double check the identity of a cultivar, consolidating the expertise of ampelographers. The work is carried out in several stages, from verifying the existence of a variety in a small region, through to rehabilitation. During this session, the authors present the process that leads to the official registration of a variety. After this, IFV selection center takes over to initiate the process of selection and propagation. A specific focus within regions such as the Alps, Champagne and the South-West will provide details of the full procedure. Bia, Bouysselet, Chardonnay rose, Mecle and the aptly named Tardif, are some of the cultivars that have followed this procedure. Furthermore, a recent regulation established by INAO on “varieties of interest for adaptation purposes” might boost uptake by growers. Since 2006, 36 historical cultivars have been registered. Most of these have been neglected in the past due to late maturity, lack of sugar and high titratable acidity at harvest time. Such characteristics are today considered as positive qualities, not only in mitigation of the effects of climate change, but also as an opportunity for restoring diversity…

“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.

In wine growing regions around the world, climate change has the potential to affect vine transpiration and overall vineyard water use due to related changes in atmospheric demand and soil water deficits. Grapevines control their transpiration in response to a changing environment by regulating conductance of water through the soil-plant-atmosphere continuum. Most vineyard water use models currently estimate vine transpiration by applying generic crop coefficients to estimates of reference evapotranspiration, but this does not account for changes in vine conductance associated with water stress, nor differences thought to exist between varieties. The response of bulk stomatal conductance to daily weather variability and seasonal drought stress was studied on Cabernet-Sauvignon, Merlot, Tempranillo, Ugni blanc, and Semillon vines in a non-irrigated vineyard in Bordeaux France. Whole vine sap flow, temperature and humidity in the vine canopy, and net radiation absorbed by the vine canopy were measured on 15-minute intervals from early July through mid-September 2020, together with periodic measurement of leaf area, canopy porosity, and predawn leaf water potential. From this data, bulk stomatal conductance was calculated on 15-minute intervals, and multiple regression analysis was performed to identify key variables and their relative effect on conductance. Attention was focused on addressing multicollinearity and time-dependency in the explanatory variables and developing regression models that were readily interpretable. Variability of vapor pressure deficit over the day, and predawn water potential over the season explained much of the variability in conductance, with relative differences in response coefficients observed across the five varieties. By characterizing this conductance response, the dynamics of vine transpiration can be better parameterized in vineyard water use modeling of current and future climate scenarios.

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.