Withering of the ‘Moscato giallo’ grapes under covered space

La création officielle du groupe Experts Zonage Vitivinicole à l’O.I.V., qui s’inscrit dans la Commission Viticulture, est récente. Le Professeur Mario FREGONI en assure la présidence depuis 1998, assisté du vice-président et du secrétaire général Mario FALCETTI. Ils ont été confirmés dans leurs fonctions lors des sessions de mars 2001. Actuellement, le groupe d’experts Zonage Vitivinicole de l’O.I.V. se compose de 40 délégués, représentant 18 pays membres. La mise en place de ce groupe a tout d’abord été initiée par l’Instituto Agrario de San Michele (Italie) et l’Unité de Recherches Vigne et Vin du Centre INRA d’Angers (France). Une collaboration entre les chercheurs s’est installée très tôt, dès 1987.

Lately several works highlighted the capacity of grape cell-wall material (CWM) to interact with proanthocyanidins (PA), indicating its potential use as fining agent for red wines.1–4 However, those studies were performed by using purified PAs and very high doses of CWM (almost ten-fold higher than those used in wine industry for other commercial fining agents). The present study focuses on the applicability of CWM from Cabernet sauvignon pomace as fining agent for red wines under real winery conditions. Grapes of cultivar Cabernet sauvignon were harvested at three different maturity levels
(unripe, mature, and overripe) and used for red winemaking. The pomace of such vinifications were used as source of CWM, and applied into red wines at two different concentrations: 0.2 g/L and 2.5 g/L.

Mannoproteins (MPs) are proteoglycans from the outmost layer of yeast cell walls released into wine during alcoholic fermentation and ageing on lees processes. The use of commercial preparations of mannoproteins as additives to improve wine stability with regards to the crystallization of tartaric salts and to prevent protein haze in the case of white and rosé wines is authorized by the OIV.
Regarding red wines and polyphenols, mannoproteins are described as able to improve their colloidal stability and modulate the astringent effect of condensed tannins. The latter interact with salivary proteins forming insoluble aggregates that cause a loss of lubrication in the mouth and promote a drying and puckering sensation. However, neither the interaction mechanisms involved in mannoproteins capacity to impact astringency nor the structure-function relationships related to this property are fully understood.

Amarone is an Italian red wine produced in the Valpolicella area, in north-eastern Italy. Due to its elaboration with withered grapes, Amarone is a rather unique example of dry red wine. However, there is very limited data so far concerning the volatile composition of commercial Amarone wines, which also undergo a cask aging of 2-4 years before release.

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.