Observation and modeling of climate at fine scales in wine-producing areas

In a previous zoning program (1998-2002), climatic and pedological factors were able to distinguish 14 terroir within the Soave DOC area where wine characteristics are well recognizable. Nevertheless, in the past vinegrowers identified several vineyards where a better quality of the grapes and wines could be obtained. So, « beyond the zonation » will aim to suggest a new methodology to characterise the Cru, starting with 15 vineyards that were selected in the Soave Classico DOC area. In the year 2005, a meteorological station was positioned in each vineyard and temperature data were collected; because of the limited area of investigation, only 3 rain sensors were set up.

Eger wine region is located on the northern border of grapevine cultivation zone. In the cool climate, terroir selection is one of the foundations of quality wine making. However, climate change will have a significant impact on these high value-added vineyards. This study presents a case study from 2021 and 2022 with the investigation of three grape varieties (Kadarka, Syrah, Furmint). The experiment was conducted in a steep-sloped vineyard (Nagy-Eged hill) with a southern exposure.

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.

Wine is a solution containing abundant volatile compounds which contribute to their aroma. Many of them are produced by yeast as metabolism by-products. Different yeast strains produce different volatile profiles. The possibility of studying the evolution of volatile compounds during fermentation, using sampling methods that not alter the volume of fermentation media, is of great interest. In spite of this, non-invasive methods to monitoring the evolution of volatile profile during fermentation have been seldom used. The goals of this work were to use by first time the headspace sorptive extraction (HSSE) as non-invasive method to monitor the evolution of volatile profiles throughout alcoholic fermentation and to study the changes on volatile profiles produced by Saccharomyces cerevisiae and Lachancea thermotolerans during fermentation of a must with high sugar content.

The Portuguese wine production is characterized by wide yield fluctuations, causing considerable implications in the economic performance of this sector. The possibility of predicting the yield in advance is crucial as it enables preliminary planning and management of the available resources. The present work aims to study and evaluate two different techniques for the assessment of vine fertility. vineyards.