Simgi® platform as a tool for the study of wine active compounds in the  gastrointestinal tract

It is important to quantify the effect of potential crop on vine water constraint in order to adapt vine-growing consulting and vine management to the Mediterranean climate conditions

Chasselas is a refined grape variety renowned for its subtlety and its remarkable ability to reflect terroir characteristics [1]. Typically consumed young, it is appreciated for its low acidity and delicate fruity and floral aromas.

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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).

Due to the global demand for terroir wines, the winemaking industry has focused attention on exploiting the local yeast microflora of each wine growing region to express the regional character and enhance the sensory profile of wines such as varietal typicity and aroma complexity. The objective of the present study was to isolate and compare the indigenous strains of Saccharomyces cerevisiae present in different vineyards in the Mesogeia – Attiki wine region (Greece), evaluate their impact on chemical composition and sensory profile of Savatiano wines and select the most suitable ones for winemaking process.