Red Grenache variety in Rhône Valley : impact of “terroir” and vintages on the aromatic potential of the grapes

AIM Verdicchio and Lugana are two Italian white wines produced in the Marche and Garda lake regions respectively. They are however obtained using grape varieties sharing the same genetic background, locally known as Verdicchio in Marche and Trebbiano di Soave in Garda. Anecdotal evidence suggests that these two wine types exhibit distinctive aroma features. The aim of this work was to explore the existence of a recognizable odour profile for Lugana and Verdicchio, and whether specific aroma chemical markers could be identified. METHODS 13 commercial wines, 6 Lugana and 7 Verdicchio were used. Sensory analysis was done using sorting task methodology, assessing only odor similarities. A total of 53 volatile compounds were identified and quantified GC-MS analysis. Aging behaviors were also evaluated after an accelerated aging at 40 ° C for 3 months. RESULTS HCA analysis of sorting task data identified indeed two groups: one characterized by floral and minty notes and mostly associated with Lugana wines, the other characterized by spicy and toasted aromas and mostly associated with Verdicchio. From a chemical point of view, major differences between the two wines types were observed for cis-3-hexenol, methionol, phenylethyl alcohol, and geraniol.

In this video recording of the IVES science meeting 2021, Simone D. Castellarin (University of British Columbia, Wine Research Center, Wine Research Centre, Vancouver, Canada) speaks about the effects of water deficit on secondary metabolites in grapes and wines. This presentation is based on an original article accessible for free on OENO One.

L’entreprise viticole Concha y Toro S.A. gère environ 600 ha de vignes dans la Vallée du Maipo (A.O. Valle del Maipo). L’objectif est celui de caractériser spatialement ces vignobles et leur occupation du sol environnante. Le choix s’est porté vers la démarche de zonage viticole par l’analyse spatiale, utilisant des traitements d’images satellitaires afin d’avoir une vision synoptique de la zone à moindres coûts et délais. Un système d’informations géographiques (SIG) est construit à partir des données suivantes : cartes topographiques, géologique, fond cadastral numérique, images satellitaires. Un modèle numérique de terrain est par ailleurs construit à une résolution de 25 m à partir des cartes topographiques.

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).

Aims: DOSAVIÑA® was developed with the aim of helping farmers to determine optimal volume rates for spray applications in vineyards. The final developed tool is a good example of bringing research to end users.