Early Elgo Demetra: the new pink table variety seedless with big berry and resistant

In recent years, Uruguay has embraced the Albariño grape variety (Vitis vinifera L.) as one of the most promising for commercial growth. Originally cultivated in Galicia and northern Portugal, Albariño has risen to prominence in the global wine market, driving strong demand and significantly increasing grape prices [1].

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. Climate change and the demand for reducing inputs, including chemical compounds, present significant challenges for perennial fruit crops like grapes and apples.

With alcohol consumption steadily declining, the growing popularity of dry january, a fiercely competitive environment, high dry matter inflation, economic upheavals, commercial uncertainties… The wine industry must adapt and offer products that meet consumer expectations, without denying their historical singularities.

In this audio recording of the IVES science meeting 2022, Thibaut Verdenal (Agroscope, Pully, Switzerland) speaks about managing nitrogen balance in cover-cropped vineyard. This presentation is based on an original article accessible for free on OENO One.