Changing New Zealand climate equals a changing New Zealand terroir?

Our research aimed to determine the effect and efficiency of foliar application of urea on the phenolic composition of Tempranillo Blanco grapes. The field experiment was carried out in 2019 and 2020 seasons and the plot was located in D.O.Ca Rioja (North of Spain). The vineyard was Vitis vinifera L. Tempranillo Blanco and grafted on Richter-110 rootstock. The treatments were control (C), whose plants were sprayed with water and three doses of urea: plants were sprayed with urea 3 kg N/ha (U3), 6 kg N/ha (U6) and 9 kg N/ha (U9). The applications were performed in two phenological stages, pre-veraison (Pre) and veraison (Ver). Also, each of the treatments was repeated one week later. Control and treatments were performed in triplicate and arranged in a randomised block design. Grapes were harvested at optimum ripening stage. High-performance liquid chromatography was used to analyse the phenolic composition of the grapes. Finally, the results obtained from the analytical determinations – flavonols, flavanols and non-flavonoid (hydroxybenzoic acids, hydroxycinnamic acids and stilbenes) – were studied statistically by analysis of variance. The results showed that, in 2019, U6-Pre and U9-Pre treatments increased the hydroxybenzoic acid content in grapes, and also all foliar treatments applied at Pre enhanced the stilbene concentration. Moreover, U3-Ver was the only treatment that rose flavonol and stilbene contents in the Tempranillo Blanco grapes. In 2020, all treatments applied at Pre enhanced the flavonol concentration in grapes. Furthermore, U3-Pre and U9-Pre treatments increased stilbene content in grapes. Nevertheless, the hydroxybenzoic acid content was improved by U6-Ver and U9-Ver and besides, hydroxycinnamic acid concentration in grapes was increased by all treatments applied at Ver. In conclusion, the lower and highest dose of urea (U3 and U9), applied at pre-veraison, were the best treatments to improve the Tempranillo Blanco grape phenolic composition.

Using viticultural and enological techniques to increase aromatics in white wine is a prized yet challenging technique for commercial wine producers. Equally difficult are challenges encountered in hastening phenolic maturity and thereby increasing color intensity in red wines. The ability to alter organoleptic and visual properties of wines plays a decisive role in vintages in which grapes are not able to reach full maturity, which is seen increasingly more often as a result of climate change. A new, yeast-based product on the viticultural market may give the opportunity to increase sensory properties of finished wines. Manufacturer packaging claims these yeast derivatives intensify wine aromas of white grape varieties, as well as improve phenolic ripeness of red varieties, but the effects of this application have been little researched until now. The current study applied the yeast derivative, according to the manufacture’s instructions, to the leaves of both neutral and aromatic white wine varieties, as well as on structured red wine varieties. Chemical parameters and volatile aromatics were analyzed in grape musts and finished wines, and all wines were subjected to sensory analysis by a tasting panel. Collective results of all analyses showed that the application of the yeast derivative in the vineyard showed no effect across all varieties examined, and did not intensify white wine aromatics, nor improve phenolic ripeness and color intensity in red wine.

Winegrowing regions recognized as protected designations of origin (PDOs) are closely tied to well defined geographic locations with a specific set of pedoclimatic attributes and strictly regulated by legal specifications. However, climate change is increasingly threatening these regions by changing local conditions and altering winegrowing processes. The vulnerability to these changes is largely heterogenous across different winegrowing regions because it is determined by individual characteristics of each region, including the capacity to adapt to new climatic conditions and the sensitivity to climate change, which depend not only on natural, but also socioeconomic and legal factors. Accurate vulnerability assessments therefore need to combine information about adaptive capacity and climate change sensitivity with projected exposure to new climatic conditions. However, most existing studies focus on specific impacts neglecting important interactions between the different factors that determine climate change vulnerability. Here, we present the first comprehensive vulnerability assessment of European wine PDOs that spatially combines multiple indicators of adaptive capacity and climate change sensitivity with high-resolution climate projections. We found that the climate change vulnerability of PDO areas largely depends on the complex interactions between physical and socioeconomic factors. Homogenous topographic conditions and a narrow varietal spectrum increase climate change vulnerability, while the skills and education of farmers, together with a good economic situation, decrease their vulnerability. Assessments of climate change consequences therefore need to consider multiple variables as well as their interrelations to provide a comprehensive understanding of the expected impacts of climate change on European PDOs. Our results provide the first vulnerability assessment for European winegrowing regions at high spatiotemporal resolution that includes multiple factors related to climate exposure, sensitivity, and adaptive capacity on the level of single winegrowing regions. They will therefore help to identify hot spots of climate change vulnerability among European PDOs and efficiently direct adaptation strategies.

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.

The Barossa zone is arguably one of the most well-recognised wine producing regions in Australia and internationally; known mainly for the production of its distinct Shiraz wines. However, within the broad Barossa geographical delimitation, a variation in terroir can be perceived and is expressed as sensorial and chemical profile differences between wines. This study aimed to explore the sub-division classification across the Barossa region using chemical and sensory measurements. Shiraz grapes from 4 different vintages and different vineyards across the Barossa (2018, n = 69; 2019, n = 72; 2020, n = 79; 2021, n = 64) were harvested and made using a standardised small lot winemaking procedure. The analysis involved a sensory descriptive analysis with a highly trained panel and chemical measurement including basic chemistry (e.g. pH, TA, alcohol content, total SO2), phenolic composition, volatile compounds, metals, proline, and polysaccharides. The datasets were combined and analysed through an unsupervised, clustering analysis. Firstly, each vintage was considered separately to investigate any vintage to vintage variation. The datasets were then combined and analysed as a whole. The number of sub-divisions based on the measurements were identified and characterised with their sensory and chemical profile and some consistencies were seen between the vintages. Preliminary analysis of the sensory results showed that in most vintages, two major groups could be identified characterised with one group showing a fruit-forward profile and another displaying savoury and cooked vegetables characters. The exploration of distinct profiles arising from the Barossa wine producing region will provide producers with valuable information about the regional potential of their wine assisting with tools to increase their target market and reputation. This study will also provide a robust and comprehensive basis to determine the distinctive terroir characteristics which exist within the Barossa wine producing region.