Enhancing plant defense: carbon dots for efficient spray-induced gene silencing 

La maîtrise de la typicité du vin s’élabore au niveau local ou communal d’une exploitation viticole et/ou d’une cave, unité de vinification. La cave coopérative de Saint-Hilaire­-d’Ozilhan (AOC Côtes-du-Rhône), dont le territoire communal s’étend sur une superficie de 1 670 ha, couvre près de 310 ha cultivés en vigne. Elle réalise des vinifications «au terroir», en utilisant des regroupements d’unités de sol en 9 unités de terroir potentiellement viticoles, définies en s’appuyant sur la parenté des substrats. Diverses sélections d’une même unité peuvent aboutir aussi à des vins différents, ce qui suggère une hétérogénéité spatiale de certaines unités définies.

Managing grapevines according to the practices of Precision Agriculture (PA), may prove to be an asset in the hands of the modern grape growers.

There are fundamentally two different ways in which indications of geographical origin (igos) can be protected. The us approach favors the pre-existing trademark system through collective marks (cms), while the eu approach favors a maximalist approach via a sui generis system which promotes appellations of origin (aos). A consensus however emerges regarding the fundamental protection of origin against misleading, confusing and dilutive uses. Previous literature discusses these competing igo logics from historical, legal and international trade perspectives. In this paper, we depart from the field of social sciences, in particular from recent advancements in the well-established literature on proximities, in order to provide a reflection on the different logics underpinning the aos and cms systems.

Mannoproteins (MPs) with different structure of their polysaccharide part (branching, substitutions, …) were used to better understand the impact of characteristics of the usual structure of MPs when interacting with Grape Seed Tannins (ST). 

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.