Viticultural zoning of central chile based on bioclimatic indexes and the impact of climate warming

The aim of this study was to evaluate the evolution of different chemical parameters and sensory impact on red wine during maturation in barrels or with new technologies

Brandy de Jerez (BJ) is a spirit drink made exclusively from spirits and wine distillates and is characterized by the use of casks for aging that previously contained Sherries. The quality and sensory complexity of BJ depend on the raw materials and some factors: grape variety, conditions during processing the wine and its distillation, as well as the aging in the cask. Therefore, the original compounds of the grapes from which it comes are of great interest being in most cases the Airén variety. Their relationship with the quality of the musts and the wines obtained from them has been studied (1) and varies each year of harvest depending on the weather conditions (2).

Aims: Wine perceived quality lies on a number of different factors. Among these, sensory features, which are in turn dependent on chemical composition, play a primary role. There is traditionally a great emphasis on producing wines that have specific sensory profiles, particularly aroma, that reflect identity features connected to the place and the variety of origin. In the case of high quality

Dans la tradition classique, les vins mousseux sont le produit d’assemblage des vins d’origine différent. La choix de la typologie du moussage (brut, extra-brut, dosage zéro, etc.) généralement est une conséquence des résultats organoleptiques atteints à la fin de le période d’affinement en bouteille.

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).