Evaluation des aptitudes œnologiques des raisins rouges avec l’étude de certains nouveaux indices de maturité phénolique

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.

Context and purpose of the study. Globally, vineyard cultivation uses conventional methods to manage pests, diseases and increase yield.

Atypical aging (ATA) is a white wine fault characterized by the appearance of notes of wet rag, acacia blossoms and naphthalene, along with the vanishing of varietal aromas. 2-aminoacetophenone (AAP) – a degradation compound of indole-3-acetic acid (IAA) – is regarded as the main sensorial and chemical marker responsible for this defect. About the origin of ATA, a stress reaction occurring in the vineyard has been looked as the leading cause of this defect. Agronomic, climatic and pedological factors are the main triggers and among them, drought stress seems to play a crucial role.[1]

By using HPLC-ESI-MS, 1H, 13C and 2D NMR, new addition products between catechin, epicatechin, caftaric acid and 3SH were characterized. Caftaric acid formed more rapidly adducts with 3SH than catechin and epicatechin in the absence of other nucleophiles.

It is important to examine the yield quality elements of table grape varieties. There are great differences in winter and summer pruning of the early sweet grape variety. For this reason, in the study, the effects of different crop loads and pruning processes on grape yield, quality characteristics and vine development in the early sweet (vitis vinifera L.) Grape variety were investigated.