Classification of the wine-growing environment of Central Mancha (Spain). First works

The complexity of the wine matrix makes the monitoring of the winemaking process crucial. Fourier Transform Infrared Spectroscopy (FTIR) along with chemometrics is considered an effective analytical tool combining good accuracy, robustness, high sample throughput, and “green character”. Portable and non-portable FTIR devices are already used by the wine industry for routine analysis. However, the analytical calibrations need to be enriched, and some others are still waiting to be thoroughly developed.

Aging on lees (AOL) has been used for wine aging for a long time, thanks to its ability to modify wine composition, improving sensory characteristics and stability. However, the prolonged contact with fermentation lees may increase the risk of developing sensory defects, due to the growth of unwanted microorganisms. Furthermore, AOL requires a large amount of work to manage bâtonnage and for topping up the barrels, significantly increasing production costs.

White wine protein haze can be prevented by removing the grape juice proteins, currently achieved by bentonite addition. To avoid wine volume loss and to minimizes aroma stripping, degrading haze-forming proteins in wine with proteases is a particularly interesting alternative to bentonite. In the present study, two fungal proteases treatments combined with different heating (50, 60, 72 °C) + refreshing steps, were applied on Gewürztraminer grape juice, and compared to bentonite treatments. The impact of these 19 treatments on the wine haze risks was determined by using two heat tests at 50 °C (heating during 30 to 120 min) and 80 °C (heating during 5 to 60 min). The protein contents and compositions were also estimated using the SDS-PAGE + densitometric integration techniques.

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).

Genetic variants known to produce single residue missense mutations have been associated with phenotypic traits of commercial interest in grapevine. This is the case of the K284N substitution in VviDXS1 associated with muscat aroma, or the R197L in VviAGL11 causing stenospermocarpic seedless grapes. The impact of such mutations on protein structure, stability, dynamics, interactions, or functional mechanism can be studied by computational methods, including our pyDock scoring, previously developed. For this, knowledge on the 3D structure of the protein and its complexes with other proteins and biomolecules is required, but such knowledge is not available for virtually none of the proteins and complexes in grapevine.