Cultivation of grapes Chardonnay in soils with management practices biodynamic and conventional

Serbian autochthonous vine varieties Smederevka (for white wines) and Prokupac (for rosé and red wines) are the primary representatives of typical characteristics of wines and terroir of numerous wine-growing areas in Serbia. In the past, these varieties were the leading vine varieties, however, as the result of globalization of winemaking and the trend of consumption of wines from widely prevalent vine varieties, they were replaced by introduced international varieties. Smederevka and Prokupac vine varieties are characterized by later time of grape ripening, and relative sensitivity to low temperatures. Climate conditions can be a restrictive factor for production of high-quality grapes and wine and for the spatial spreading of these varieties in hilly continental wine-growing areas.
This paper focuses on the spatial analysis of changes of main climate parameters, in particular, analysis of viticultural bioclimatic indices that were determined for the purposes of viticulture zoning of wine-growing areas in the period 1961-2010, and those same parameters determined for the current, that is, referential climate period (1988-2017). Results of the research, that is, analysis of climate changes indicate that the majority of examined climate parameters in the Oplenac wine-growing district improved from the perspective of Smederevka and Prokupac vine varieties. These studies of climate conditions indicate that changes of analyzed climate parameters, that is, bioclimatic indices will be favorable for cultivation of varieties with later grape ripening times and those more sensitive to low temperatures, such as the autochthonous vine varieties Smederevka and Prokupac, therefore, it is recommended to producers to more actively plant vineyards with these varieties in the territory of the Oplenac wine-growing district.

The wine sector is of great relevance and tradition in Mediterranean countries, however, it may be most susceptible to climate change. In recent years, wine production is facing changes worldwide, both at environmental as well as commercial levels, due to global warming and the shift in consumers’ preferences. Wine growers and wine makers are in search of solutions that allow to face these new challenges. One of the most promising initiatives in the long term is the introduction of new plant materials, specifically intraspecific hybridizations between premium varieties that may improve traditional germplasm in its adaptation to climate change. These inter-varietal crosses have the potential to generate quality wines, whilst maintaining the regional typicity, and constitute an attractive alternative for the consumer due to their sensory attributes. In this study, we have evaluated wines from 29 intraspecific Garnacha x Tempranillo hybrids in two different locations, with the aim to assess their oenological potential and sensory attributes. Thirteen of the selections were white and 16 were red. Microvinifications were conducted with two or three replications depending on grape availability. Conventional oenological parameters were determined for all wines. The sensory evaluation and hedonic scores were given by five experts. Red selections obtained higher quality scores than white ones. Among the white selections with higher quality scores, GT-41 Varea and GT-159 Varea outstand, due to their high total acidity and high malic acid content. Regarding red selections, GT-57 Varea and GT-57 UR were perceived as higher in quality, highlighted for their moderate alcoholic and high anthocyanin content. Our results indicate that intraspecific hybridization may be a powerful tool for adapting traditional cultivars to climate change in Rioja.

Currently, the main goal of agriculture is to promote the resilience of agricultural systems in a sustainable way through the improvement of use efficiency of farm resources, increasing crop yield and quality under climate change conditions. This last is expected to drastically modify plant growth, with possible negative effects, especially in arid and semi-arid regions of Europe on the viticultural sector. In this context, the monitoring of spatial behavior of grapevine during the growing season represents an opportunity to improve the plant management, winegrowers’ incomes, and to preserve the environmental health, but it has additional costs for the farmer. Nowadays, UAS equipped with a VIS-NIR multispectral camera (blue, green, red, red-edge, and NIR) represents a good and relatively cheap solution to assess plant status spatial information (by means of a limited set of spectral vegetation indices), representing important support in precision agriculture management during the growing season. While differences between UAS-based multispectral imagery and point-based spectroscopy are well discussed in the literature, their impact on plant status estimation by vegetation indices is not completely investigated in depth. The aim of this study was to assess the performance level of UAS-based multispectral (5 bands across 450-800nm spectral region with a spatial resolution of 5cm) imagery, reconstructed high-resolution satellite (Sentinel-2A) multispectral imagery (13 bands across 400-2500 nm with spatial resolution of <2 m) through Convolutional Neural Network (CNN) approach, and point-based field spectroscopy (collecting 600 wavelengths across 400-1000 nm spectral region with a surface footprint of 1-2 cm) in a plant status estimation application, and then, using Bayesian regularization artificial neural network for leaf chlorophyll content (LCC) and plant water status (LWP) prediction. The test site is a Greco vineyard of southern Italy, where detailed and precise records on soil and atmosphere systems, in-vivo plant monitoring of eco-physiological parameters have been conducted.

Vitis vinifera L. ‘Gewürztraminer’ is a historical grape variety of Alto Adige (Südtirol), Italy, which is widely grown in the area of Tramin an der Weinstraße, but is also grown globally. It produces highly aromatic wines that are strongly influenced by the terroir of the vineyard sites where they are grown. This study looked at musts and young wines from ‘Gewürztraminer’ grapes harvested in seven distinct vineyards near Tramin and then processed at Cantina di Termeno, minimizing winemaking protocol variability. Samples were profiled using bidimensional gas chromatography–time-of-flight mass spectrometry, liquid chromatography coupled to electrochemical detection, and near-IR spectrometry. The data were subjected to Principle Component Analysis and Hierarchical Clustering Analysis. Sensory discriminant testing was undertaken using the sorting method with a semi-trained panel, and the data were processed using Multidimensional Scaling. Seven must/wine pairs could be distinguished based on their untargeted volatilome profiles and on sensory evaluation. As expected, there were greater differences in the volatile compounds between the wines than between the musts. The wines from vineyards 4 and 5 were nonetheless quite homogenous in terms of chemical and sensory analyses, as were the wines from vineyards 1 and 3. For the phenolic profile, differences were noted between the musts and wines of vineyards 2, 3, and 4, but the musts from vineyards 5 and 7 were similar. Sensory analysis showed the wines from vineyards 6 and 7 to be distinct from the rest. These results reinforce that the composition of ‘Gewürztraminer’ musts and wines is strongly determined by vineyard site, even in a small geographic area with high variability of the terroir (soil and microclimate), and that these differences are apparent in the flavours and aromas of the finished wines. Further confirmation would require a larger sample of wines, preferably from several vintages.

The project VINIoT pursues the creation of a new technological vineyard monitoring service, which will allow companies in the wine sector in the SUDOE space to monitor plantations in real time and remotely at various levels of precision. The system is based on spectral images and an IoT architecture that allows assessing parameters of interest viticulture and the collection of data at a precise scale (level of grape, plant, plot or vineyard) will be designed. In France, three subjects were specifically developed: evaluation of maturity, of water stress, and detection of flavescence dorée. For the evaluation of maturity, it has been decided first to work at the berry scale in the laboratory, then at the bunch scale and finally in the vineyard. The acquisition of the spectral hyperstal image as well as the reference analyzes to measure the maturity, were carried out in the laboratory after harvesting the berries in a maturity monitoring context. This work focuses on a case study to predict sugar content of three different grape varieties: Syrah, Fer Servadou and Mauzac. A robust method called Roboost-PLSR, developed in the framework of this work (Courand et al., 2022), to improve prediction model performance was applied on spectra after the acquirement of hyperspectral images. Regarding the evaluation of water stress, to work with a significant variability in terms of water status, it has been worked first with potted plants under 2 different water regimes. The facilities have allowed the supervision of irrigation and micro-climatic conditions. The regression models on agronomic variables (stomatal conductance, water potential, …) are studied. To detect flavescence dorée, the experimental plan has consisted of work at leaf scale in the laboratory first, and then in the field. To detect the disease from hyper-spectral imaging, a combination of multivariate curve resolution-alternating least squares (MCR-ALS) and factorial discriminant analysis (FDA) was proposed. This strategy proved the potential towards the discrimination of healthy and infected leaves by flavescence dorée based on the use of hyperspectral images (Mas Garcia et al., 2021).