Digitalization and valorization of the genotypic and phenotypic information retained within the FEM grapevine germplasm

Most oxidation reactions in wine require iron as a catalyst. The iron content of wine has decreased greatly in recent decades due to the use of low or no release cellar materials; however, in some cases it is still necessary to adopt winemaking practices to remove excess iron from wine, prevent its oxidation, and be able to reduce the addition of sulfur dioxide and other antioxidants.

Hydrolysable tannins resulted effective against the formation of light-struck taste (LST) in model wine [1]. The first activity of Enofotoshield project is to evaluate the effectiveness of tannins

Grape and wine phenolic compounds have been shown to be highly related to both wine quality (color, flavor, and taste) and health-promoting properties (antioxidant and cardioprotective, among others). The aim of this work was to evaluate and compare the phenolic contents of Cabernet Sauvignon wines from different geographical areas and climatic conditions, namely from Argentina, Portugal and Spain vintage 2022. In addition, the phenolic profiles of the Portuguese wines from three vintages (2020, 2021, 2022) was compared.

Aromatic composition contributes mainly to the quality aroma of white wine. A natural and gradual evolution of the aroma in the bottle occurs over storage with a very low oxygen content.

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).