Qualité des vins et Terroirs. Incidence du milieu naturel sur la composition aromatique des vins

“Sulphites” and mainly sulphur dioxide (SO2) is by far the most widely used additive (E-220/INS 220) in winemaking and likely the most difficult to replace. The well-known antioxidant, antioxidasic and antimicrobial properties of SO2 make this molecule a practically essential tool, not only in winemaking, but also in the production of other food products. The current trend in winemaking is the reduction of this unfriendly additive due to its negative effects on health and environmental. In particular, it could cause headaches and intolerance/allergic reactions in sensitive individuals. Wine is considered one of the major contributors of exposure of SO2 in the adult population, when this beverage is included in the diet.

The phenolic compounds present in the wine are responsible for reducing the risk of developing chronic diseases (cardiovascular, cancer, diabetes, Alzheimer …) because of their antioxidant activities and the presence of nutraceutical molecules with targeted biological activities. Polyphenols not only contribute to the “French paradox” but also contribute to give the wine its color, structure, aroma and allow a long-term preservation.

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.

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.

Certain grape varieties contain negligible levels of isobutyl methoxypyrazine (IBMP) in grapes. However, it has long been known that grape stems