Evaluation of state of vineyards and characterization of vineyard sites of the integrated area of Tokaj Kereskedőház ltd. in Tokaj region

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.

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.

Optimizing the use of water and improving irrigation strategies has become increasingly important in most winegrowing countries due to the consequences of climate change, which are leading to more frequent droughts, heat waves, or alteration of precipitation patterns. Optimized irrigation scheduling can only be based on a reliable knowledge of the vineyard water status.

In this context, this work aims at the development of a novel methodology, using a contactless, miniaturized, low-cost NIR spectral tool to monitor (on-the-go) the vineyard water status variability. On-the-go spectral measurements were acquired in the vineyard using a NIR micro spectrometer, operating in the 900–1900 nm spectral range, from a ground vehicle moving at 3 km/h. Spectral measurements were collected on the northeast side of the canopy across four different dates (July 8th, 14th, 21st and August 12th) during 2021 season in a commercial vineyard (3 ha). Grapevines of Vitis vinifera L. Graciano planted on a VSP trellis were monitored at solar noon using stem water potential (Ψs) as reference indicators of plant water status. In total, 108 measurements of Ψs were taken (27 vines per date).

Calibration and prediction models were performed using Partial Least Squares (PLS) regression. The best prediction models for grapevine water status yielded a determination coefficient of cross-validation (r2cv) of 0.67 and a root mean square error of cross-validation (RMSEcv) of 0.131 MPa. This predictive model was employed to map the spatial variability of the vineyard water status and provided useful, practical information towards the implementation of appropriate irrigation strategies. The outcomes presented in this work show the great potential of this low-cost methodology to assess the vineyard stem water potential and its spatial variability in a commercial vineyard.

Soil is a reservoir of microorganisms playing important roles in biogeochemical cycles and interacting with plants whether in the rhizosphere or in the root endosphere. The composition of the microbial communities thus impacts the plant health. Rhizodeposits (such as sugar, organic and amino acids, secondary metabolites, dead root cells …) are released by the roots and influence the communities of rhizospheric microorganisms, acting as signaling compounds or carbon sources for microbes. The composition of root exudates varies depending on several factors including genotypes. As most of the cultivated grapevines worldwide are grafted plants, the aim of this study was to explore the influence of rootstock and scion genotypes on the microbial communities of the rhizosphere and the root endosphere. The work was conducted in the GreffAdapt plot (55 rootstocks x 5 scions), in which the 275 combinations have been planted into 3 blocks designed according to the soil resistivity. Samples of roots and rhizosphere of 10 scion x rootstock combinations were first collected in May among the blocks 2 and 3. The quantities of bacteria, fungi and archaea have been assessed in the rhizosphere by quantitative PCR, and by cultivable methods for bacteria and fungi. The communities of bacteria, fungi and arbuscular mycorrhizal fungi (AMF) was analyzed by Illumina sequencing of 16S rRNA gene, ITS and 28S rRNA gene, respectively. The level of mycorrhization was also evaluated using black ink coloration of newly formed roots harvested in October. The level of bacteria, fungi and archaea was dependent on rootstock and scion genotypes. A block effect was observed, suggesting that the soil characteristics strongly influenced the microorganisms from the rhizosphere and root endosphere. High-throughput sequencing of the different target genes showed different communities of bacteria, fungi and AMF associated with the scion x rootstock combinations. Finally, all the combinations were naturally mycorrhized. The root mycorrhization intensity was influenced by the rootstock genotype, but not by the scion one. Altogether, these results suggest that both rootstock and scion genotypes influence the rhizosphere and root endophytic microbiomes. It would be interesting to analyze the biochemical composition of the rhizodeposition of these genotypes for a better understanding of the processes involved in the modulation of these microbiomes. Moreover, crossing our data with the plant agronomic characteristics could provide insights into their roles on plant fitness.

Protected Designation of Origin “Jumilla” (PDO Jumilla) is located in the Spanish provinces of Albacete and Murcia, in the South-eastern part of the Iberian Peninsula, where most of the models predict a severe impact of climate change in next decades. PDO Jumilla covers an area of 247,054 hectares, of which more than 22,000 hectares