Comprehensive evaluation of grape composition at winery receiving areas often requires multiple measurements to ensure representativeness, as well as the use of analytical techniques that are time-consuming and involve sample preparation.

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).

We propose here a brand new large routine microbiological analysis method intended for oenology, in flow cytometry, using high performance equipment and triple selective cell staining, activated by fluorescence. The results and practical applications of the method are presented: Brettanomyces (Dekkera) Monitoring, fermentations monitoring, bottling and enological practices monitoring.The method allow a complete new microbiological tool for wine industry.The method has been accredited ISO 17025 in our laboratories.

The influence of dipping pretreatments on drying of ‘Pedro Ximenez’ grapes, destined to the elaboration of sweet wines, in chamber at controlled temperature, has been studied. Changes in color and phenolic composition of raisins produced were observed during the process of raisining.

Foliar application of urea has proven to be an effective method for increasing the amino acid content in grapes, especially when the vineyard has additional nitrogen needs. These treatments can prevent problems of stucking fermentation during winemaking.