Caratterizzazione vitivinicola delle “Terre del Piacenziano” ricomprese nella zona D.O.C. “colli piacentini” attraverso l’analisi sensoriale dei vini prodotti

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.

In response to changes in their environment, grapevines regulate transpiration using various physiological mechanisms that alter conductance of water through the soil-plant-atmosphere continuum. Expressed as bulk stomatal conductance at the canopy scale, it varies diurnally in response to changes in vapor pressure deficit and net radiation, and over the season to changes in soil water deficits and hydraulic conductivity of both soil and plant. It is necessary to characterize the response of conductance to these variables to better model how vine transpiration also responds to these variables. Furthermore, to be relevant for vineyard-scale modeling, conductance is best characterized using data collected in a vineyard setting. Applying a crop canopy energy flux model developed by Shuttleworth and Wallace, bulk stomatal conductance was estimated using measurements of individual vine sap flow, temperature and humidity within the vine canopy, and estimates of net radiation absorbed by the vine canopy. These measurements were taken on several vines in a non-irrigated vineyard in Bordeaux France, using equipment that did not interfere with ongoing vineyard operations. An inverted Penman-Monteith equation was then used to calculate bulk stomatal conductance on 15-minute intervals from July to mid-September 2020. Time-series plots show significant diurnal variation and seasonal decreases in conductance, with overall values similar to those in the literature. Global sensitivity analysis using non-parametric regression found transpiration flux and vapor pressure deficit to be the most important input variables to the calculation of bulk stomatal conductance, with absorbed net radiation and bulk boundary layer conductance being much less important. Conversely, bulk stomatal conductance was one of the most important inputs when calculating vine transpiration, further emphasizing the need for characterizing its response to environmental changes for use in vineyard water use modeling.

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.

Soil is a reservoir of microorganisms playing important roles in biogeochemical cycles and interacting with plants whether in the rhizosphere or in the root endosphere. The composition of the microbial communities thus impacts the plant health. Rhizodeposits (such as sugar, organic and amino acids, secondary metabolites, dead root cells …) are released by the roots and influence the communities of rhizospheric microorganisms, acting as signaling compounds or carbon sources for microbes. The composition of root exudates varies depending on several factors including genotypes. As most of the cultivated grapevines worldwide are grafted plants, the aim of this study was to explore the influence of rootstock and scion genotypes on the microbial communities of the rhizosphere and the root endosphere. The work was conducted in the GreffAdapt plot (55 rootstocks x 5 scions), in which the 275 combinations have been planted into 3 blocks designed according to the soil resistivity. Samples of roots and rhizosphere of 10 scion x rootstock combinations were first collected in May among the blocks 2 and 3. The quantities of bacteria, fungi and archaea have been assessed in the rhizosphere by quantitative PCR, and by cultivable methods for bacteria and fungi. The communities of bacteria, fungi and arbuscular mycorrhizal fungi (AMF) was analyzed by Illumina sequencing of 16S rRNA gene, ITS and 28S rRNA gene, respectively. The level of mycorrhization was also evaluated using black ink coloration of newly formed roots harvested in October. The level of bacteria, fungi and archaea was dependent on rootstock and scion genotypes. A block effect was observed, suggesting that the soil characteristics strongly influenced the microorganisms from the rhizosphere and root endosphere. High-throughput sequencing of the different target genes showed different communities of bacteria, fungi and AMF associated with the scion x rootstock combinations. Finally, all the combinations were naturally mycorrhized. The root mycorrhization intensity was influenced by the rootstock genotype, but not by the scion one. Altogether, these results suggest that both rootstock and scion genotypes influence the rhizosphere and root endophytic microbiomes. It would be interesting to analyze the biochemical composition of the rhizodeposition of these genotypes for a better understanding of the processes involved in the modulation of these microbiomes. Moreover, crossing our data with the plant agronomic characteristics could provide insights into their roles on plant fitness.

Climate change effects in Languedoc include an expected rise in temperatures, increased evapotranspiration as well as more severe and frequent climatic hazards, such as frost, drought periods and heat waves. For winegrowers theses phenomena impact both yield and quality, resulting in more frequent unbalanced wines. Research on identified mitigation tools for vineyard management is necessary to improve resilience of grapevine agrosystems. Varietal assortment is one of them. This study focuses on agronomic and oenologic potential of 14 foreign varieties grown in Languedoc French region. Fourteen grapevine varieties were monitored during 2021 from June until harvest on eight different sites, some of which occurring on more than one site adding up to 21 different modalities: 7 white varieties Alvarinho B, Assyrtiko B (2), Malvasia Istriana B, Parellada B, Verdejo B, Verdelho B, Xarello B, and 7 black varieties Saperavi N (2), Touriga nacional N, Baga N, Aleatico N, Montepulciano N (2), Primitivo N (3), Calabrese N (3). Varietals were compared through the following parameters: phenology was assessed by using the information collected in the Database Network of French Vine Conservatories (INRAE-SupAgro-IFV, 2005-2015). The number of inflorescences for shoots from secondary buds and bourillons and suckers were observed to assess post-bud break frost tolerance potential. Grapevine water status was studied through stem water potential measurement, observation of foliage symptoms of drought, and 𝛿13C on must. Frequencies and intensities of downy mildew, powdery mildew, and black rot attacks were estimated before harvest on leaves and clusters and botrytis at harvest to assess disease susceptibilities. Berry composition was monitored from end of veraison until harvest. Yield and mean bunch weight were also calculated. Varieties were then ranked on a 1-4 scale for each parameter and compared through PCA. Forty two stations of the Mediterranean basin were compared by PCA with the Multicriteria Climatic Classification indicators in order to confront the collected information during 2021 campaign to the hypothesis that plants coming from dry and hot regions are genetically adapted to such climatic conditions.