Defining gene regulation and co-regulation at single cell resolution in grapevine

In the last years the application of genomic tools to the analysis of gene expression during grape berry development generated a huge amount of transcriptomic data

Recent regulations concerning alcoholic beverages have prompted producers to revise their product labels to incorporate nutritional information. In this context, qr codes containing such information, known as e-labels, are now being employed on wine labels for the first time.

Acid aspergillopepsins-i (ap-i) have been suggested for use in winemaking due to their ability to degrade proteins, which reduces haze formation and the necessity for bentonite to achieve protein stability. These endopeptidases cleave non-terminal amino acid bonds of proteins, resulting in their degradation.

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).

In the bottom of Val d’Illasi (Verona province), one of the major valleys which passes through the Lessini mountains, viticulture is widely extended. In the territory belonging to Illasi and Tregnago villages, which includes ca. 1100 ha of vineyards, devoted to produce Soave and Valpolicella DOC wines, an experimental survey was conducted on a network of twenty five reference vineyards.