Xylem vessel blockages in grape pedicel growing in tropical climate observed by microtomography

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Wineries may randomly reject fruit from vineyards near wild fires exposed to smoke. It is difficult to determine if fruit has been compromised in quality when exposed to smoke

A new framework for the segmentation and characterization of row crops on remote sensing images has been developed and validated for vineyard monitoring. This framework operates on any high-resolution remote sensing images since it is mainly based on geometric information. It aims at obtaining maps describing the variation of a vegetation index such as NDVI along each row of a parcel.

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).

The quantity and distribution of polyphenols in musts play a fundamental role in the white winemaking. This is because these substances are exposed to oxidation reactions, which are catalysed by the polyphenol oxidase (PPO), leading to a decrease in the quality of the wines produced. PPO is inactivated by SO2, but currently, due to the restrictions of the legislation, other methodologies are being investigated. Ultra-High Pressure Homogenization (UHPH) is a non-thermal physic technology that exerts an ultrahigh pressure pumping (>200 MPa) of a fluid through a valve in a continuous system.