UHPLC-HRMS analysis for the evaluation of formation and degradation of polysulfides in wine 

Global change in climate affect regional climates and hold implications for viticulture worldwide. Despite numerous studies on the impact of projected global warming on different regions

Les cycles journaliers du potentiel hydrique foliaire (Ψl) ont été établis toutes les heures, pour différents stades phénologiques, sur deux localités et en fonction de différentes mesures de la température de l’air et du déficit en pression de vapeur (VPD). De faibles valeurs pour ces 2 paramètres ont été enregistrées tout au long de la saison à

Chardonnay is the world’s most planted white grape variety and has met a great commercial success for decades.

L’essai a été effectué dans un vignoble du cépage Nero d’Avola greffé sur 1103 Paulsen dans un terroir de la D.O.C Alcamo en Sicile. Le système de conduite des vignes était à espalier, la taille à cordon coursonné et l’irrigation à goutte a goutte. On a été confrontés trois types de traitements: A) vignes non irriguées; B) vignes irriguées quand le

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).