The application of soil biological indicators to support soil conservation practices and landscape quality in viticulture

Wineries may randomly reject fruit from vineyards near wild fires exposed to smoke. It is difficult to determine if fruit has been compromised in quality when exposed to smoke

he use of high-power ultrasound (US) is proving of great interest to the oenological industry due to its effects in the improvement of wine organoleptic characteristics, especially in terms of color [1, 2].

Aim: The aim of this report is to present evidence on the potential of Greek and Cypriot grape varieties to serve as a sustainable solution to mitigate climate change.

Methods and Results: The work provides a review of recent works involving Greek and Cypriot varieties’ performance under high temperatures and increased dryness.

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.

In an experiment located at Quinta da Cavadinha, Sabrosa, Douro Region the behaviour of the varieties Touriga Nacional (TN), Tinta Barroca (TB), Touriga Franca