Prediction of astringency in red wine using tribology approach to study in-mouth perception

This study aimed to explore an alternative fate of varietal thiols by identifying and characterising cis-2-methyl-4-propyl-1,3-oxathiane

Interspecific hybrid winegrapes are of growing interest in the context of climate change based on their disease resistance and cold hardiness. In addition to a need for increased understanding of their chemical composition, there is little empirical evidence on the consumer perception of non-vinifera wine. Phenolic compounds, and particularly color, play an important organoleptic and quality determination role in wine, but can vary significantly in interspecific hybrid wines compared to wines produced from Vitis vinifera cultivars [1, 2, 3]. Anecdotally, the variation in anthocyanin species, interactions, and concentrations in interspecific hybrids could result in a variance from“vinifera-like” wine color.

The aim of this ongoing study is to evaluate the degree of adaptability of grapevine scion:rootstock combinations to different conditions of water constraint. Here we present results from the young vine development phase, using three scenarios of water constraint that were implemented from planting. The experimental vineyard was established in 2020 and the data presented will cover the 2021/2022 and 2022/2023 seasons. The experiment consisted of the cultivars Pinotage (PIN), Shiraz (SHI) and Cabernet Sauvignon (CAB), grafted on two rootstocks, Richter 110 (R110) and USVIT-8-7 (US87).

Dans une région comme la Toscane, zone dans laquelle sont produits certains des meilleurs vins italiens et du monde, la province d’Arezzo a actuellement une importance relativement marginale

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).