Prove preliminari dl caratterizzazione del vino gutturnio dei colli piacentini

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.

Grapevines are very sensitive to weather conditions. Excessively hot and dry periods trigger the activation of survival mechanisms, such as reduction of crop transpiration and the redistribution of water. Monitoring these mechanisms is, therefore, essential to better understand the grapevine water dynamics and maximize water-use efficiency.

Anticipation in the possible responses of grapevines to environmental variations is key to adjust field work in view of a more effective management. This idea has been the driving force behind the current work, which seeks to understand the interaction patterns of the vine with its habitat throughout the growing cycle.

Pruning is one essential vineyard management activity whose main purpose is to regulate plant growth and vigour, modulating berry size, and consequently, wine quality. In Chilecito, La Rioja Province, Argentina, Torrontés Riojano stands as the only autochthonous variety for winemaking, yielding golden and aromatic berries and distinctive muscatel-tasting wines. This white cultivar, resulting from the natural cross between Moscatel de Alejandría x Criolla Chica, is traditionally trained in “parral” (horizontal trellis system), aimed to manage vigorous canopies. This project constitutes the first study on the influence of pruning intensity on Torrontés Riojano growth habit and berry quality.

The Pomerol vineyard, located 35 km east of Bordeaux, covers around 800 ha on the left bank of the Isle. There is a system of fluvial terraces with more or less coarse gravel and pebble spreading, resting on a Tertiary substratum ranging from the Middle to Upper Eocene to the Lower Oligocene (Dubreuilh, 1993). This interweaving of terraces of varying thickness results in a brutal superposition of differentiated materials which give rise to various types of soil. Several site studies in this sector of the Libounais show significant morphological and analytical differences from one point to another (Guilloux et al ., 1978; Duteau, 1982; Van Leeuwen et al.., 1989). The distribution of the soils of the Pomerol vineyard was studied and resulted in a cartography at 1/25000th (Merouge, 1995).