An internet-based gis application for vineyard site assessment in the U.S. and matching grape variety to site

In grape berry pedicel, xylem hydraulic conductance can be impaired by blockage deposition in the lumen of xylem elements. However, the varietal difference of the interruptions has not yet been characterized. In this preliminary work, we utilized synchrotron x-ray computed microtomography experiments performed at MOGNO beamline (LNLS – Brazil) to identify possible blockage sites in natural grape pedicel xylem. For this, we imaged dehydrated pedicel’s stem portion from the Niagara Rosada variety in three different phenological stages (Pre-veraison (PreV), veraison (V) and post-veraison (PostV). The reconstructed tridimensional images with a voxel size of 1.16 µm were segmented for the identification of xylem vessel lumens. After analysing one pedicel stem per stage, we identified 658 vessels without occlusion throughout his axial plane and 41 in which we could identify possible interruptions.

L’appellation d’origine contrôlée repose sur une définition précise de l’aire de production du raisin. Cette délimitation définie par l’Institut National des Appellations d’Origine est proposée par des experts choisis pour leurs compétences dans le domaine de la connaissance de la relation terroir – vins, après avis du syndicat de défense de chaque AOC.

Plants in their natural environment are in continuous interaction with large numbers of potentially pathogenic and beneficial microorganisms. Depending on the microbe, plants have evolved a variety of resistance mechanisms that can be constitutively expressed or induced. Phytoalexins, which are biocidal compounds of low to medium molecular weight synthesized by and accumulated in plants as a response to stress, take part in this intricate defense system.1,2
One of the limitations of our knowledge of phytoalexins is the difficulty of analyzing their spatial responsiveness occurring during plant- pathogen interactions under natural conditions.

Water deficits limit yields and this is one of the negative aspects of climate change. However, this applies particularly when emphasis is on biomass production (e.g. for crops like maize, wheat, etc.)

Aim: Through machine-learning modelling of plant water status from environmental characteristics, this work aims to develop a model able to predict grape phenolic composition in space and time to guide selective harvest decisions at the estate scale.