Haplotype-resolved genome assemblies of Chasselas and Ugni Blanc

The genetic material preservation is a priority issue in winemaking research. The recovery of minority grape varieties can control the genetic erosion, contributing also to preserve wine typical characteristics. In D.O.Ca. Rioja (Spain) the number of grown white varieties has been very limited, representing Viura the 91% of the cultivated white grape area in 2005, while the others, Garnacha Blanca and Malvasía riojana, hardly were grown. For this reason, a recovery and characterization study of plant material was carried out in this region. In 2008, the results obtained allowed the authorization of three minority white varieties: Tempranillo Blanco, Maturana Blanca and Turruntés.

The grape volatile compounds determine the wine quality and typicity [1]. Thus, looking for agronomic tools to improve its composition it is of great interest in the sector [2]

Context and purpose of the study. The wine industries face significant challenges from two highly detrimental viruses: leafroll and red blotch.

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).

Soil mulching is an interesting strategy to reduce soil evaporation, assist in weed control, improve soil structure and organic content, increase soil water infiltration, and decrease diurnal temperature fluctuations