Long term influence of a cover crop in the agronomic and oenological performance of CV. Chardonnay

Varietal innovation is a major lever for meeting the challenges of the agro-ecological transition of vi-neyards and their adaptation to climate change. To date, selection work has already begun in the Bordeaux region through the Newvine project. The aim of this project is to create new vine varieties with resistance to mildew and powdery mildew, adapted to the climatic conditions of the Bordeaux region and enabling the production of wines that are in line with consumer tastes and the expected typicity of Bordeaux wines.

During wine alcoholic fermentation, yeasts produce volatile aroma compounds from sugar and nitrogen metabolism. Some of the metabolic pathways leading to these compounds have been known for more than a century.

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).

The landscape is defined by the European convention of the landscape (Florence, October 20, 2000) like part of the territory as perceived by the populations, whose character results from the action of natural and/or human factors and their interrelationships. This convention is based on the contribution cultural, ecological, environmental, social of the landscapes and aims at a reinforcement of the tools of protection and valorization in particular in the agricultural policies, of regional planning and town planning. Moreover, it encourages a step of identification and qualification of the landscapes and underlines the need for developing the sensitizing and the training of the actors concerned.

Major factors involved in wine quality and typicity are soil type, climatic conditions, plant material (rootstock and cultivar), vineyard management practices and winemaking conditions.