How sensor technologies combined with artificial intelligence increase the efficiency in grapevine breeding (research): current developments and future perspectives

STICS est un modèle de culture développé à l’INRA (France) depuis 1996. Il simule les bilans de carbone, d’eau et d’azote dans le système culture-sol, piloté par des données climatiques journaliéres. Il calcule à la fois des variables agricoles (rendement en quantité et qualité) et environnementales (pertes en eau et en azote). Une des originalités de STICS est son adaptabilité à de nombreuses cultures (herbacées, ligneuses, annuelles, pérennes) rendue possible par le choix de paramètres génériques et d’options de formalismes. Le travail présenté traite, dans un premier temps, des spécificités de STICS pour la vigne en terme de bilan trophique, de fonctionnement énergétique et hydrique et d’estimation des teneurs en sucre en en eau du raisin. Nous montrons ensuite diverses sorties du modèle qui permettent de caractériser des terroirs du vignoble des Côtes du Rhône.

Characteristics related to the climate and the soil of Montefalco in the centre of Italy have been defined in order to evaluate their influence on the red cv.

This elaboration presents vine spa has precious contribution of social development health and well being in culture of wine regions. The majority of the vine-spas in the world draw raw materials from the vineyard; both for cosmetics treatments and for dishes in their restaurants. Vitis vinifera vine provides fresh grapes for dishes and massages, seeds and oil from the seeds, as well as the leaves, and its extracts, and above all the wine.

Knowledge on the reflectance spectrum of soil is potentially useful since it carries information on soil chemical composition that can be used to the planning of agricultural practices. If compared with analytical methods such as conventional chemical analysis, reflectance measurement provides non-destructive, economic, near real-time data. This paper reports results from reflectance measurements performed by spectroradiometry on soils from two vineyards in south Brazil. The vineyards are close to each other, are on different geological formations, but were subjected to the same management. The objective was to detect spectral differences between the two areas, correlating these differences to variations in their chemical composition, to assess the technique’s potential to predict soil attributes from reflectance data.To that end, soil samples were collected from ten selected vine parcels. Chemical analysis yield data on concentration of twenty-one soil attributes, and spectroradiometry was performed on samples. Chemical differences significant to a 95% confidence level between the two studied areas were found for six soil attributes, and the average reflectance spectra were separated by this same level along most of the observed spectral domain. Correlations between soil reflectance and concentrations of soil attributes were looked for, and for ten soil traits it was possible to define wavelength domains were reflectance and concentrations are correlated to confidence levels from 95% to 99%. Partial Least Squares Regression (PLSR) analyses were performed comparing measured and predicted concentrations, and for fifteen out of 21 soil traits we found Pearson correlation coefficients r > 0.8. These preliminary results, which have to be validated, suggest that variations of concentration in the investigated soil attributes induce differences in reflectance that can be detected by spectroradiometry. Applications of these observations include the assessment of the chemical content of soils by spectroradiometry as a fast, low-cost alternative to chemical analytical methods.

A 3-year study was conducted in the Vaud vineyard (Switzerland) to evaluate the effects of « terroir » on the ecophysiology and fruit compostion of Vitis vinifera L. cv.