Measurement of synthetic solutions imitating alcoholic fermentation by dielectric spectroscopy

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.

This study aims to create an updated, agile viticultural climate index (similar to the Winkler Index) by performing in-depth analyses of current and historical data from industry partners in several major winegrowing regions. The Winkler Index was developed in the early twentieth century based on analysis of various grape-growing regions in California. The index uses heat accumulation (i.e. Growing Degree Days) throughout the growing season to determine which grape varieties are best suited to each region. As viticultural regions are increasingly subject to the complexity and uncertainty of a changing climate, a more rigorous, agile model is needed to aid grape growers in determining which cultivars to plant where. For the first phase of this study, 21 industry partners throughout Napa Valley shared historical phenology, harvest, viticultural practice, and weather data related to their Cabernet sauvignon vineyard blocks. To complement this data, berry samples were collected throughout the 2021 growing season from 50 vineyard blocks located throughout 16 American Viticultural Areas that were then analyzed for basic berry chemistry and phenolics. These blocks have been mapped using a Geographic Information System (GIS), enabling analysis of altitude, vineyard row orientation, slope, and remotely sensed climate data. Sampling sites were also chosen based on their proximity to a weather station. By analyzing historical data from industry partners and data specifically collected for this study, it is possible to identify key parameters for further analysis. Initial results indicate extreme variability at a high spatial resolution not currently accounted for in modern viticultural climate indices and suggest that viticultural practices play a major role. Using the structure of data collection and analyses developed for the first phase, this project will soon be expanded to other wine regions globally, while continuing data collection in Napa Valley.

A gradual decline in vineyards has been observed over the past twenty years worldwide. This might be explained by the climate change, practices change or the increase of dieback diseases. To increase the longevity of vines, we studied the impact of different pruning strategies in four adult and four young vineyards located in France and Spain. In France, vineyards were planted with Cabernet franc on 3309C while Spanish trials were planted with Tempranillo grafted on 110R. Vegetative expression, yield, quality of berries and wood vessels conductivity were measured. The distribution of vegetative expression, yield and berry composition between primary and secondary vegetation were quantified. Finally, tomography was used to evaluate the implication of the treatments on sap flows.
First results show that i) the respectful pruning leads to an increase of 30 to 50% more secondary shoots than the aggressive pruning in France and between 15 and 20% in Spain, ii) there is no major effect on the yield over the first two years following the implementation of the new pruning practices, although the proportion of clusters from suckers is higher on the respectful pruning method. On young vines, the development of the trunk according to a respectful pruning leads to a loss of harvest 2 years after planting. This is due to the removal, on the future trunk, of the green suckers which carrying bunches. This operation carried out in spring rather than during winter pruning, would promote a better leaf / fruit balance when the plant comes into production, and could lead to better hydraulic conduction in the vessels of the trunk. Maintaining these trials for several years will provide more robust data to assess the impact of these practices on the vines over the long term.

The mechanization of vineyard work originally led to a reduction in planting densities due to the lack of machinery adapted to the vineyard. The current availability of specific machinery makes it possible to establish higher planting densities. In this work, three planting densities (1.40×0.80 m, 1.80×1 m and 2.20×1.20 m, corresponding to 8928, 5555 and 3787 plants/ha respectively) were studied with four varieties autochthonous of Galicia (northwestern Spain): Albariño and Treixadura (white), Sousón and Mencía (red). The vines were trained in a vertical shoot positioning system using a single Royat cordon, and pruned to spurs with two buds each. Agronomic data (yield, pruning wood weight, Ravaz index) and oenological data in must were collected. The higher planting density (1.40×0.80 m) had no significant effect on grape yield per vine in white varieties, although production per hectare was much higher due to the greater number of plants. In red varieties, this planting density resulted in a significantly lower production per vine, compensated by the greater number of plants. In addition, it significantly reduced the Brix degree in the must of the Albariño, Treixadura and Sousón varieties, and increased the total acidity in the latter two and Mencía. It also caused an increase in extractable and total anthocyanins and IPT in red grapes. The effects of high planting density on grapes are of great interest for the adaptation of varieties in the context of climate change. In the future, it could be advisable to modify the limits imposed by the appellations of origin on the planting density of these varieties in order to obtain more balanced wines.

To digitally record and present all the origins of Austrian wines in the same perfect and clear way was the motivation for the Austrian Wine Marketing Board (Austrian Wine) to start with the project in 2018. In June 2021 the results were presented to the public in an online viewer showing all the designations of Austrian wine, available at https://austrianvineyards.com in a largely barrier-free manner. The online viewer provides tailored individual maps fitted to the respective zoom level. The smallest unit of wine-origins in Austria is called Ried and is displayed in a plot-specific manner highlighting areas under vine. Information on the Ried include administrative district, winegrowing municipality, cadastral municipality, large collective vineyard site, specific winegrowing region, generic winegrowing region, winegrowing area and, in many cases, an illustrative picture. Complementary data on the size, elevation (minimum-maximum), orientation (in 8 sectors plus flat) and gradient (minimum, maximum, average) are based on the area under vine according to the EU’s Integrated Administration and Control System. Additional information covers climate data. The diagrams are taken from the monthly breakdown of data in the annals of the Central Institute for Meteorology and Geodynamics, Austria provide a display of values for air temperature, precipitation, and sunshine hours for the reference year and the long-term average. Seasonal aggregated data on temperature, precipitation, and sunshine hours complete the display. Short descriptions with emphasis on geology and soil, field name in historical maps, etymology of the denomination, and main planted variety complements the available information for the main designations in the online viewer. These descriptions are compiled by winegrowers, geologists, historians, and journalists. All the information and data can be extracted to a pdf-file. Printed vineyard maps are also available. Missing content regarding wine origins in Styria will be completed in winter 2021/22.