Management of varietal thiols in white and rosé wines using biotechnical tools

During postharvest management, the metabolism of fruits remains active and continuous physico-chemical changes occur. Ozone treatment has an elicitor effect on secondary metabolites and the treatment conditions can influence the grape response to the stress (Bellincontro et al., 2017; Botondi et al., 2015). Regarding volatile organic compounds (VOCs), previous studies showed that ozone treatment during postharvest dehydration induces the biosynthesis of terpenes in Moscato bianco grapes (Río Segade et al., 2017). It is well known that grape VOCs greatly influence the organoleptic properties of wines, particularly terpenes in aromatic varieties.

Wine lees are the second most important wine by-product in terms of quantity after grape stalk and marc. During aging on lees, it is well known that wine lees yield compounds that act as antioxydant. However the chemical nature of the compounds involved in this behavior (except polyphenols and glutathione) has not yet been totally elucidated. The scarce knowledge of wine lees composition and their potential exploitation make them a promising candidate to obtain new antioxidant products to be used in winemaking. In this study, an eco-sustainable approach to obtain lees extracts exhibiting antioxidant capacity is proposed. Such extracts could be used in a global enological strategy of sulfites level reduction.

Dans le cadre de TerclimPro 2025, Esther Fouillet a présenté un article IVES Technical Reviews. Retrouvez la présentation ci-dessous ainsi que l’article associé : https://ives-technicalreviews.eu/article/view/8318

La région de la Vallée du São Francisco, situe à 9º S, est en train d’augmenter la production des vins fins les dernières années. La région présente climat du type tropical semi-aride (climat viticole à variabilité intra-annuelle selon le Système CCM Géoviticole : “très chaud, à nuits chaudes et à sécheresse forte à sub-humide” en fonction

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).