Effet terroir et arômes des muscats

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Insufficient levels of malate and lack of acidity in commercial grape cultivars (V.vinifera) hinders the quality of fruit grown in warm climates. Conversely, excessive levels of malate and sourness in wild Vitis grape, leads to unpalatable fruit and complicates the introgression of valuable disease resistant alleles through breeding. Nonetheless, albeit decades of research, knowledge regarding the molecular regulation of malate levels in grape remains limited.

Agriculture is one of the largest contributors to environmental pollution and causing significant impacts on human health, ecosystems, and resource availability.

Wine varietal aroma is the result of a mixture of compounds formed or liberated from specific grape-aroma precursors. Their liberation/formation from their specific precursors can occur spontaneously by acid catalyzed rearrangements or hydrolysis or by the action of the yeast enzymatic activities. The influence of yeast during fermentation on the production of these volatile compounds has been widely studied however, the effect of this influence during aging is not fully understood. In order to evaluate these processes several indirect strategies have been used to study aroma precursors although they are not useful to understand the chemistry of the process.

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).