Biovi: a research program for reducing chemical input in vine and wine

Une étude a été menée pendant neuf ans sur deux vignes non-irriguées de Sauvignon blanc commercialisés, plantées à différentes localités (A et B) dans le district de Stellenbosch. Deux parcelles expérimentales, situées sur deux formations géologiques différentes, ont été identifiées au sein de chaque vignoble. A chaque localité une des

Sunburn results from a combination of excessive photosynthetically active radiation (PAR) and UV radiation and temperature that can be exacerbated by other stress factors such as water deficit. Sunburn is a physiological disorder that affects the visual and organoleptic properties of grapes. The appearance of brown and necrotic spots severely affects the commercial value of the fruit, and in extreme cases, significantly decreases yield. This damage occurs with some frequency in sensitive varieties such as Graciano.

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.

The unique characteristics of terroir play a fundamental role in shaping the identity and quality of wines, influencing the aromatic complexity of young wines and their long-term aging potential. The volatile compounds responsible for these aromas are crucial to identifying and appreciating a given wine.

AIM: the aim of this study was to develop a method for fine-scale temperature zoning. The effect of temperature variability on vine phenology and grape composition was assessed in the production area of Saint-Emilion