Winemaking areas recognized as protected designations of origin (PDOs) shape important economic, environmental and cultural values that are tied to closely defined geographic locations. To preserve wine products and wine-growing practices adopted in different PDOs these areas are strictly regulated by legal specifications. However, quality viticulture is increasingly under pressure from climate change, which is altering the local conditions of many winegrowing areas. Therefore, maintaining traditional wine products will require the adoption of tailored adaptation strategies, including possible changes in the legal regulation of protected wines. To this end, it is necessary to have a comprehensive knowledge on PDOs including their extension, products and allowed practices. While there have been efforts to build databases that summarize the characteristics for individual wine PDO areas and to quantify the related effects of climate change, much information is still included only in the official documentation of the EU geographical indication register and has never been collected in a comprehensive manner. With this study we aim at filling this gap by building a spatial inventory of European wine PDOs that supports decision making in viticulture in the context of climate change. To map and characterize European wine PDOs, we analysed their legal documents and extracted relevant information useful for climate change adaptation. The output consists of a comprehensive geographical dataset that identifies the boundaries of all 1200 European wine PDOs at unprecedented spatial resolution and includes a set of legally binding regulations, such as authorized vine varieties, maximum yields and planting density. The inventory will allow researchers to analyse the impacts of climate change on European wine PDOs and support decision makers in developing tailored adaptation strategies. This includes, among others, the evaluation of new vineyard site selection, the expansion of cultivated varieties or the authorization of irrigation in vineyards.

Climate change and rising atmospheric carbon dioxide concentration is a concern for agriculture, including viticulture. Studies on elevated carbon dioxide have already been on grapevines, mainly taking place in greenhouses using potted plants or using field grown vines under higher CO2 enrichment, i.e. >650 ppm. The VineyardFACE, located at Hochschule Geisenheim University, is an open field Free Air CO2 Enrichment (FACE) experimental set-up designed to study the effects of elevated carbon dioxide using field grown vines (Vitis vinifera L. cvs. Riesling and Cabernet Sauvignon). As the carbon dioxide fumigation started in 2014, the long term effects of elevated carbon dioxide treatment can be investigated on berry ripening parameters and fruit metabolic composition.
The present study aims to investigate the effect on fruit composition under a moderate increase (+20%; eCO2) of carbon dioxide concentration, as predicted for 2050 on both Riesling and Cabernet Sauvignon. Berry composition was determined for primary (sugars, organic acids, amino acids) and secondary metabolites (anthocyanins). Special focus was given on monitoring of berry diameter and ripening rates throughout three growing seasons. Compared to previous results of the early adaptative phase of the vines [1], our results show little effect of eCO2 treatment on primary metabolites composition in berries. However, total anthocyanins concentration in berry skin was lower for eCO2 treatment in 2020, although the ratio between anthocyanins derivatives did not differ.
[1] Wohlfahrt Y., Tittmann S., Schmidt D., Rauhut D., Honermeier B., Stoll M. (2020) The effect of elevated CO2 on berry development and bunch structure of Vitis vinifera L. cvs. Riesling and Cabernet Sauvignon. Applied Science Basel 10: 2486

Newer sequencing technologies have allowed for the addition of microbes to the story of terroir. The same environmental factors that influence the phenotypic expression of a crop also shape the composition of the microbial communities found on that crop. For fermented goods, such as wine, that microbial community ultimately influences the organoleptic properties of the final product that is delivered to customers. Recent studies have begun to study the biogeography of wine-associated microbes within different growing regions, finding that communities are distinct across landscapes. Despite this new knowledge, there are still many questions about what factors drive these differences. Our goal was to quantify differences in yeast communities due to management style between seven pairs of conventional and biodynamic vineyards (14 in total) throughout Oregon, USA. We wanted to answer the following questions: 1) are yeast communities distinct between biodynamic vineyards and conventional vineyards? 2) are these differences consistent across a large geographic region? 3) can differences in yeast communities be tied to differences in metabolite profiles of the bottled wine? To collect our data we took soil, bark, leaf, and grape samples from within each vineyard from five different vines of pinot noir. We also collected must and a 10º brix sample from each winery. Using these samples, we performed 18S amplicon sequencing to identify the yeast present. We then used metabolomics to characterize the organoleptic compounds present in the bottled wine from the blocks the year that we sampled. We are actively in the process of analysing our data from this study.

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.

Making high quality but affordable Pinot noir (PN) wine is challenging in most terroirs and New Zealand’s (NZ) situation is no exception. To increase the probability of making highly typical PN wines producers choose to grow grapes in cool climates on lower fertility soils while adopting labour intensive practices. Stringent yield targets and higher input costs necessarily mean that PN wine cost is high, and profitability lower, in line-priced varietal wine ranges. To understand the reasons why higher yielding vines are perceived to produce wines of lower quality we have undertaken an extensive study of PN in NZ. Since 2018, we established a network of twelve trial sites in three NZ regions to find individual vines that produced acceptable commercial yields (above 2.5kg per vine) and wines of composition comparable to “Icon” labels. Approximately 20% of 660 grape lots (N = 135) were selected from within a narrow juice Total Soluble Solids (TSS) range and made into single vine wines under controlled conditions. Principal Component Analysis of the vine, berry, juice and wine parameters from three vintages found grape berry mass to be most effective clustering variable. As berry mass category decreased there was a systematic increase in the probability of higher berry red colour and total phenolics with a parallel increase in wine phenolics, changed aroma fraction and decreased juice amino acids. The influence of berry size on wine composition would appear stronger than the individual effects of vintage, region, vineyard or vine yield. Our observations support the hypothesis that it is possible to produce PN wines that fall within an “Icon” benchmark composition range at yields above 2.5kg per vine provided that the Leaf Area:Fruit Weight ratio is above 12cm2 per g, mean berry mass is below 1.2g and juice TSS is above 22°Brix.