Zonazione aziendale nel territorio del Chianti classico e valorizzazione dei vini

This work aimed to evaluate the evolution of phenolic compounds during white winemaking process up to bottling and 12 months storage, together with the influence of different antioxidant strategies

The challenges of the century for viticulture relate to coping with climate change and the loss of biodiversity in a downturning socio-economic context. Now more than ever, the vine and wine industry needs to be resilient to maintain and ensure a future for its heritage. An innovation of capital importance, in line with recently published research, deals with developing new methods of training our inherited and newly planted vineyards to better withstand environmental variations such as drought and heatwaves but also unevenly distributed rains and temperatures.

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.

What if, in 25 years, most wines were dealcoholized and flavored ? What if vines were only cultivated to combat erosion, store carbon, and provide anthocyanins…? What if climate change completely changed the list of vine varieties cultivable for wine production in France? What if food stores had completely disappeared in favor of virtual platforms? And if… because the long-term future is not predetermined and therefore not knowable, because the future is open to several possibilities, because the future does not emerge from nothing but from the present which conceals heavy trends and weak signals, prospective approaches make it possible to consider the room for maneuver that actors have to promote the advent of a future, which we can hope to be chosen, at least in part.

The wooden barrel is a key factor in enology, since wine chemical composition and sensory properties changes significantly in contact with the barrel[1]. Today’s highly competitive market constantly demands new differentiated products and wineries search innovations continuously.
Wood selection is crucial: barrels stability to keep constant their contribution and the result on products, and additional and differentiated wood contributions to impact their new products. Oak wood selection has traditionally been carried out using parameters such as specie, location and grain, however, it goes one step further nowadays. Large cooperage work with non-destructive techniques that allow classifying oak wood quickly and easily according to their organoleptic contribution[2].