Arsenic in soil, leaves, grapes and wines

Three-dimensional functional-structural root architecture models, which decompose the root system architecture (RSA) into elementary developmental processes such as root emission, axial growth, branching patterns and tropism have become useful tools for (i) reconstructing in silico the spatial and temporal dynamics of root systems in a soil volume, (ii) analyzing their genotypic diversity and plasticity to the environment, and (iii) overcoming the bottleneck associated with their visualization and measurement in situ. Here, we present an original work on RSA phenotyping and modelling in grapevine. First, we developed 2D image-based analysis pipelines to quantify morphological and architectural traits in young grafts. Second, we parametrized and validated the 3D root model Archisimple on two rootstock genotypes (RGM, 1103P) grafted with V. vinifera Cabernet-Sauvignon and grown in different controlled conditions (rhizotrons, pots, tubes).

Climate change is introducing a high variability on grape ripening, causing uncertainty, excessive spending on pesticides and eventually frustrating results in terms of the quality of the vintage, with the increasingly frequent appearance of aromatic problems associated with overripeness, raisining and greenness, which sometimes only appear in bottled wines.

La maturité optimale est définie en fonction du style de vin désiré, qui est fonction du marché. Le sol et le climat ont un effet sur la typicité des vins. Le niveau qualitatif des raisins et des vins, et le potentiel pour obtenir différents styles de vin est déterminé par l’association des caractéristiques naturel du terroir et les technologies mises en

Les facteurs physiques et biologiques du milieu naturel affectant la production viticole de la R.D.O. “Condado de Huelva” et quelques relations les concernant sont étudiés dans les systèmes de la production vinicole ; le bon fonctionnement du Vignoble ayant besoin par ailleurs, du concours d’autres facteurs (Reynier, 1989 ; Paneque et al., 1996, a,b).

Estimation of vineyard leaf area index (LAI) is an important aspect for the winegrowers. However, tracking and monitoring are difficult tasks due to time constraints. Satellite and unmanned aerial vehicle (UAV) imaging have become a practical monitoring method for LAI. Nevertheless, for a proper LAI determination, the image’s spatial resolution is a key factor, since low-resolution images are incapable of distinguishing between adjacent vines due to the large area covered in each pixel, this leads to misinterpretation or generalisation of vineyard information.