Impact of microclimate on berry quality parameters of white Riesling (Vitis vinifera L.)

In vineyard management, the block is considered today as the technical work unit. However, considerable variability can exist inside a block with regard to physiological parameters, such as vigour, particularly because of soil heterogeneity. To represent this variability spatially, many measurements have to be taken, which is costly in both time and money. High resolution remote sensing appears to be an efficient tool for mapping intra-block heterogeneity.

Currently, the greatest challenge for vine growers is to improve the yield and quality of grapes by minimizing costs and environmental impacts. This goal can be achieved through a better knowledge of vineyard spatial variability. Traditional platforms such as airborne, satellite and unmanned aerial vehicles (UAVs) solutions are useful investigation tools for vineyard site specific management.

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.

Une étude préliminaire des situations météorologiques journalières a été réalisée pour l’Afrique du Sud et pour les mois de février (période de maturation des raisins dans la Province occidentale du Cap), à l’image de la classification synoptique réalisée aux latitudes tempérées en France (Jones & Davis, 2000), afin d’étudier les relations entre le climat et la viticulture à des latitudes plus basses.

Brandy de Jerez (BJ) is a spirit drink made exclusively from spirits and wine distillates and is characterized by the use of casks for aging that previously contained Sherries. The quality and sensory complexity of BJ depend on the raw materials and some factors: grape variety, conditions during processing the wine and its distillation, as well as the aging in the cask. Therefore, the original compounds of the grapes from which it comes are of great interest (1 y 2) being in most cases the Airén variety. Their relationship with the quality of the musts and the wines obtained from them has been studied (3) and varies each year of harvest depending on the weather conditions (4).