Étude des relations sol-vigne sur le vignoble de Côte Rôtie

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.

The presence of unstable proteins in wines can affect their stability and clarity. Before bottling, winemakers need to be sure that the wine is stable. A large number of stability tests have been proposed, usually based on heating a sample with a specific time-temperature couple. In practice, none is effective to accurately assess the risk of instability. Moreover, the interpretation of the results of these tests changes according to the region.

Downy mildew (Plasmopara viticola), powdery mildew (Erysiphe necator) and bunch rot (Botrytis cinerea) are the most prevalent fungal diseases in viticulture.

Aromas are one of the key points in food analysis since they are related to character, quality and consequently consumer acceptance. It is not different in the winery industry, where the aromatic profile is a combination of viticultural and oenological practices. Based on the development of more aromatic clones and on the potential to produce sparkling wines at Caldas, in the southern region of Minas Gerais (Brazil) (21°55´S and 46°23´W, altitude 1,100m), the aim of this work was the determination of volatile compounds in six different clones of Chardonnay grape berries to better understand which compounds add bouquet to the wine, and additionally comprehend the impacts of the edaphoclimatic and annual conditions on the improvement of grape-growing and winemaking practices.

The project VINIoT pursues the creation of a new technological vineyard monitoring service, which will allow companies in the wine sector in the SUDOE space to monitor plantations in real time and remotely at various levels of precision. The system is based on spectral images and an IoT architecture that allows assessing parameters of interest viticulture and the collection of data at a precise scale (level of grape, plant, plot or vineyard) will be designed. In France, three subjects were specifically developed: evaluation of maturity, of water stress, and detection of flavescence dorée. For the evaluation of maturity, it has been decided first to work at the berry scale in the laboratory, then at the bunch scale and finally in the vineyard. The acquisition of the spectral hyperstal image as well as the reference analyzes to measure the maturity, were carried out in the laboratory after harvesting the berries in a maturity monitoring context. This work focuses on a case study to predict sugar content of three different grape varieties: Syrah, Fer Servadou and Mauzac. A robust method called Roboost-PLSR, developed in the framework of this work (Courand et al., 2022), to improve prediction model performance was applied on spectra after the acquirement of hyperspectral images. Regarding the evaluation of water stress, to work with a significant variability in terms of water status, it has been worked first with potted plants under 2 different water regimes. The facilities have allowed the supervision of irrigation and micro-climatic conditions. The regression models on agronomic variables (stomatal conductance, water potential, …) are studied. To detect flavescence dorée, the experimental plan has consisted of work at leaf scale in the laboratory first, and then in the field. To detect the disease from hyper-spectral imaging, a combination of multivariate curve resolution-alternating least squares (MCR-ALS) and factorial discriminant analysis (FDA) was proposed. This strategy proved the potential towards the discrimination of healthy and infected leaves by flavescence dorée based on the use of hyperspectral images (Mas Garcia et al., 2021).