Effects of soil characteristics on manganese transfer from soil to vine and wine

The objective of the work described here is the elaboration of a map of the different types of vineyard soils that to guide the famers in the choice of the most productive vine rootstocks and varieties. 90 vineyard soils profiles were analysed in the entire territory of the Origen Denominations of Valdepeñas. The sampling was carried out in 2018 (June to October) by making a sampling grid, followed by photointerpretation and control in the field. The studied soils can be grouped into 9 different soil types (according to FAO 2006 classification): Leptosols, Regosols, Fluvisols, Gleysols, Cambisols, Calcisols, Luvisols and Anthrosols. A map showing the soil distribution with different type of soils has been made with the ArcGIS program. Regarding to the choice of rootstock, Calcisoles are soils with a high active limestone content, so the rootstocks used in these soils must be resistant to this parameter; Luvisols are deep soils with high clay content, so they will support vigorous rootstocks. Because the cartographic units are composed of two or more subgroups, with are associated in variable proportions, 9 different soil associations have been established; Unit 1: Leptosols, Cambisols and Luvisols (80%, 15% and 5% respectively); Unit 2: Cambisols with Regosols and Luvisols (40%, 30% and 30% respectively); Unit 3: Cambisols and Gleysols with Regosols (40%, 40% and 20% respectively); Unit 4: Regosols with Cambisols, Leptosols and Calcisols (40%, 30%, 15% and 15% respectively); Unit 5: Cambisols, Leptosols, Calcisols and Regosols (25% each of them); Unit 6: Luvisols with Cambisol and Calcisols (80%, 10% and 10% respectively); Unit 7: Luvisols and Calcisols with Cambisols (40%, 40% and 20% respectively); Unit 8: Calcisols with, Cambisols and Luvisols (80%, 10% and 10% respectively); Unit 9: Anthrosols. These study allow to elaborate the first map of vineyard soils of this Protected Designation of Origin in Castilla-La Mancha.

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…

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.

Winegrowing regions recognized as protected designations of origin (PDOs) are closely tied to well defined geographic locations with a specific set of pedoclimatic attributes and strictly regulated by legal specifications. However, climate change is increasingly threatening these regions by changing local conditions and altering winegrowing processes. The vulnerability to these changes is largely heterogenous across different winegrowing regions because it is determined by individual characteristics of each region, including the capacity to adapt to new climatic conditions and the sensitivity to climate change, which depend not only on natural, but also socioeconomic and legal factors. Accurate vulnerability assessments therefore need to combine information about adaptive capacity and climate change sensitivity with projected exposure to new climatic conditions. However, most existing studies focus on specific impacts neglecting important interactions between the different factors that determine climate change vulnerability. Here, we present the first comprehensive vulnerability assessment of European wine PDOs that spatially combines multiple indicators of adaptive capacity and climate change sensitivity with high-resolution climate projections. We found that the climate change vulnerability of PDO areas largely depends on the complex interactions between physical and socioeconomic factors. Homogenous topographic conditions and a narrow varietal spectrum increase climate change vulnerability, while the skills and education of farmers, together with a good economic situation, decrease their vulnerability. Assessments of climate change consequences therefore need to consider multiple variables as well as their interrelations to provide a comprehensive understanding of the expected impacts of climate change on European PDOs. Our results provide the first vulnerability assessment for European winegrowing regions at high spatiotemporal resolution that includes multiple factors related to climate exposure, sensitivity, and adaptive capacity on the level of single winegrowing regions. They will therefore help to identify hot spots of climate change vulnerability among European PDOs and efficiently direct adaptation strategies.

Agriculture, natural resource management and the production and sale of products such as wine are increasingly data-driven activities. Thus, the use of remote and proximal crop and soil sensors to aid management decisions is becoming commonplace and ‘Agtech’ is proliferating commercially; mapping, underpinned by geographical information systems and complex methods of spatial analysis, is widely used. Likewise, the chemical and sensory analysis of wines draws on multivariate statistics; the efficient winery intake of grapes, subsequent production of wines and their delivery to markets relies on logistics; whilst the sales and marketing of wines is increasingly driven by artificial intelligence linked to the recorded purchasing behaviour of consumers. In brief, there is data everywhere!

Opinions will vary on whether these developments are a good thing. Those concerned with the ‘mystique’ of wine, or the historical aspects of terroir and its preservation, may find them confronting. In contrast, they offer an opportunity to those interested in the biophysical elements of terroir, and efforts aimed at better understanding how these impact on vineyard performance and the sensory attributes of resultant wines. At the previous Terroir Congress, we demonstrated the potential of analytical methods used at the within-vineyard scale in the development of Precision Viticulture, in contributing to a quantitative understanding of regional terroir. For this conference, we take this approach forward with examples from contrasting locations in both the northern and southern hemispheres. We show how, by focussing on the vineyards within winegrowing regions, as opposed to all of the land within those regions, we might move towards a more robust terroir zoning than one derived from a mixture of history, thematic mapping, heuristics and the whims of marketers. Aside from providing improved understanding by underpinning terroir with data, such methods should also promote improved management of the entire wine value chain.