Hydraulic redistribution and water movement mechanisms in grapevines

In the Cognac appellation, the production of white wines is almost exclusively dedicated to elaborate Charentaise eaux-de-vie. In this sense, the quality of Cognac eaux-de-vie intrinsically depends on the quality of the base wines subjected to the distillation stage. In this context, the production of these base wines differs from those of classic white wines to release particular organoleptic properties during the distillation stage.

By dissecting the root system architecture (RSA) into its underpinning components (e.g. root emission, axial growth, radial growth, branching, root direction or tropism) and identifying the relationships between them, functional-structural 3D root models are promising tools for analyzing the diversity and complexity of root system phenotypes with Genotype × Environment interactions. The model parameters are assumed to be synthetic traits, less influenced by the environment, and consequently with less polygenic architectures than the integrative RSA traits they drive. Root models can serve as a basis for in silico development of root system ideotypes by highlighting the developmental processes and parameters that most likely influence RSA fitness.

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.

Cette communication sera basée sur les résultats d’une étude auprès des consommateurs réalisée par la société G3 pour l’I.N.A.O. sur les attitudes des consommateurs vis à vis des produits de terroir et des A.O.C. et sur un mémoire de DEA soutenu par Monsieur J-C. DURIEUX à l’Université de Paris X Nanterre, consacré aux variables explicatives du comportement d’achat des vins A.O.C.

According to the vintage, it may be difficult for vine growers to make a decision regarding the type of wine in relation with the soils.