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

Saccharomyces uvarum has interesting properties that can be exploited for the production of fermented beverages. Particularly, the cryotolerance and capacity to produce high amounts of volatile compounds offers new opportunities for the wine industry.

The recovery of ancestral or minority vine varieties has been gaining great interest in recent years, among other reasons because it is likely that some of these varieties, due to the fact that they are found in relict areas, have a greater potential for adaptation to external factors (biotic or abiotic) and can minimize the effects that climate change is causing in viticulture. Varieties that can be grown at altitude are currently being sought to combat rising temperatures and prolonged extreme drought conditions. In Catalonia, the Pyrenean expansion of vineyard cultivation is documented from the 10th century and has been related to the “small climatic optimum” (9th-12th centuries) and also to seigniorial power.[1] But different adverse climatic periods and the arrival of Phylloxera by the late 19th century made many of these crops disappear.[2]

Increasing drought is the most important impact of the ongoing climate change in the Mediterranean Basin, and it is predicted to result in productivity decreases and changes in grape quality.

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).

Must fermentation is a complex process influenced by various factors, especially microbiological activities. The characteristics and quality of the resulting wine are closely linked to the stages that unfold throughout this progression.