Vineyard microclimate alterations induced by black mulch through transcriptome reshaped the flavoromics of Cabernet Sauvignon

Etant lié au sol et aux conditions atmosphériques, le statut hydrique influence la physiologie de la vigne d’une part, mais joue aussi un role important en ce qui concerne la qualité du raisin et donc du vin d’autre part. Nous avons mesuré, dans la région de Stellenbosch, le statut hydrique sur des pieds de Sauvignon Blanc non irrigués, implantés sur 2 terroirs différents, l’un froid, l’autre plus chaud.

The consequences of the global climate change in the vitiviniculture are revealed as a gap between phenolic and technological grape maturities, higher grape sugar concentration that leads to high wine alcohols levels, lower acidities and high pH values, among others. The unbalanced phenolic maturity caused in this scenario leads to harsh astringency and to instable colour of wines. Previous studies have reported that the addition of yeast mannoproteins (MPs) to wines may have positive effects on these two organoleptic properties due to their capability to interact with wine polyphenols [1]; however, studies about the effect of the pH on these interactions have not been carried out so far.

Aim: This study aims to show the application of a new methodological approach to improve the resolution of Sentinel-2A images and derived vegetation indices through the results from different vineyards. 

The main innovation in the VINIoT service is the joint use of two technologies that are currently used separately: vineyard monitoring using multispectral imaging and deployed terrain sensors. One part of the system is based on the development of artificial intelligence algorithms that are feed on the images of the multispectral camera and IoT sensors, high-level information on water stress, grape ripening status and the presence of diseases. In order to obtain algorithms to determine the state of ripening of the grapes and avoid losing information due to the diversity of the grape berries, it was decided to work along the first year 2020 at berry scale in the laboratory, during the second year at the cluster scale and on the last year at plot scale. Different varieties of white and red grapes were used; in the case of Galicia we worked with the white grape variety Treixadura and the red variety Mencía. During the 2020 and 2021 campaigns, multispectral images were taken in the visible and infrared range of: 1) sets of 100 grapes classifying them by means of densimetric baths, 2) individual bunches. The images taken with the laboratory analysis of the ripening stage were correlated. Technological maturity, pH, probable degree, malic acid content, tartaric acid content and parameters for assessing phenolic maturity, IPT, anthocyanin content were determined. It has been calculated for each single image the mean value of each spectral band (only taking into account the pixels of interest) and a correlation study of these values with laboratory data has been carried out. These studies are still provisional and it will be necessary to continue with them, jointly with the training of the machine learning algorithms. Processed data will allow to determine the sensitivity of the multispectral images and select bands of interest in maturation.

AIM: The current loss of genetic grapevine diversity is mainly due to the reduced number of varieties used for making wine. A way of preserved endangered varieties is the establishment of germplasm banks.