Yeast diversity in Vitis labrusca l. Ecosystems

AIM: Glutathione (GSH) is a non-protein thiol naturally present in grape berries and produced by yeasts during fermentation. It has a strong antioxidant activity, thus can be added during winemaking to limit the oxidative phenomena of wine, preserving sensory characteristics and stability, ultimately promoting a healthier product by reducing the need for SO2 addition.

The UN Agenda 2030 for Sustainable Development, a global plan for a better future, requires actions.

This summary follows this made by Hervé Hannin et al. Entitled “French wine sector facing climate change (part. 1) : a national strategy built on a foresight and participatory approach “. The french wine sector has taken a collective approach to the issue of climate change, and has officially submitted its strategy to the minister of agriculture in 2021. This industry policy is the result of multidisciplinary work carried out through the “laccave” project (metaprogramme accaf, inrae) and its prospective study designed to anticipate climate change in the french wine industry (aigrain p. Et al., 2016). French wine professionals decided to structure a strategy to deal with climate change du in particular to the presentation made at the 2016 OIV congress in Brazil.

The wine sector is undergoing considerable transformation, particularly as a result of climate change and increasing consumer expectations for quality products, in a globalised and increasingly competitive market.

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.