Radiative and thermal effects on fruit ripening induced by differences in soil colour

Sensory analysis of grape berries is a common tool to evaluate the degree of grape maturation and to make sound picking decisions.

La découverte d’une vigne gallo-romaine en plaine à Gevrey-Chambertin (Côte-d’Or) constitue un point important pour la compréhension de la construction des terroirs viticoles de Bourgogne. Sa situation en plaine constitue pour nous le point de départ d’une large réflexion sur la mise en place du modèle de viticulture de coteau qui prévaut en Bourgogne et sur les facteurs de ce changement de norme de qualité viticole. Les sources mobilisées pour cette approche interdisciplinaire et diachronique sont géomorphologiques, archéologiques et textuelles.

Chitosan is an effective antimicrobial agent available in the wine industry, because it ensures the control of a of spoilage microorganisms, such as Brettanomyces of lactic acid bacteria.

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.

AIM: Lactiplantibacillus plantarum species is wordwide used as starter for malolactic fermentation [1,2]. For the first time, in the present study, the use of L. plantarum (ML PrimeTM, Lallemand wine) to produce white wines with post-fermentative maceration extended until 60 days has been investigated.