Synthesis of the contribution of the Giesco (group of international experts of vitivinicultural systems for cooperation) to the study of terroirs

Due to ongoing climate change, managing vineyard diseases has become increasingly challenging in the Republic of Moldova.

Just over 150 years ago, phylloxera, daktulosphaera vitifoliae, was introduced to europe, and particularly france, from north america via imports of american vitis plants. This aphid, with its complex biology and life cycle, has spread rapidly to most vineyards, causing rapid and lethal decline of v. Vinifera vines due to the primary and secondary damage it causes to the roots. In response to this pest, and given the economic importance of the french wine sector, professional representatives organised into ‘agricultural societies’, scientists and public authorities rallied together to identify the exact causes, seek solutions and try to stem the serious socio-economic crisis that ensued.

Grapevines are grown mainly as grafts worldwide, but the rootstocks most commonly used were selected between the late 19th and early 20th centuries and are based on reduced genetic diversity[1]. In the context of climate change, it is indeed urgent to diversify the range of rootstocks with genotypes much more adapted to drier environments, than the existing ones[2]. The aim of this study was to evaluate the potential of new genetic resources for grapevine rootstock breeding programs. For this purpose, 12 American and Asian wild Vitis species (3 to 5 accessions per species = 50 accessions) were evaluated for their rooting ability and drought response.

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.

Cannonau variety is historically grown in a large Sardinia area (Jerzu district) and the vineyards are planted both in the plane and in the sloped hills reaching also 650 m of altitude a.s.l. Thus, in order to discover how climate, soil diversity and growing traditions could account for differences in grape and wine quality, this trial was carried out.