Analysis of climatic changes in different areas of Abruzzo region (Central Italy): implications for grape growing

AIM: The composition and quality of wine are directly linked to microorganisms involved in the alcoholic fermentation. Several studies have been conducted on the impact of Saccharomyces cerevisiae on volatile compounds composition after fermentation. However, if different studies have dealt with combined sensory and volatiles analyses, few works have compared so far the impact of distinct yeast strains on the global metabolome of the wine.

Spatial variability of vine productivity in winegrapes is important to characterise as both yield and quality are relevant for the production of different wine styles and products. The objectives were to understand how patterns of variability of Cabernet Sauvignon fruit composition changed over time and space, how these patterns could be characterised with indirect measurements, and how spatial patterns of the variation in fruit compositional attributes can aid in improving management. Prior to the 2017 vintage, 125 data vines were distributed across each of four vineyards in the Lodi American Viticultural Area (AVA) of California. Each data vine was sampled at commercial harvest in 2017, 2018, and 2019. Yield components and fruit composition were measured at harvest for each data vine, and maps of yield and fruit composition were produced for eight ‘objective measures of fruit quality’: total anthocyanins, polymeric tannins, quercetin glycosides, malic acid, yeast assimilable nitrogen, β-damascenone, C6 alcohols and aldehydes, and 3-isobutyl-2-methoxypyrazine. Patterns of variation in anthocyanins and phenolic compounds were found to be most stable over time. Given this relative stability, management decisions focused on fruit quality could be based on zonal descriptions of anthocyanins or phenolics to increase profitability in some vineyards. In each vineyard, dormant season pruning weights and soil cores were collected at each location, elevation and soil apparent electrical conductivity surveys were completed, and remotely sensed imagery was captured by fixed wing aircraft and two satellite platforms at major phenological stages. The data collected were used to develop relationships among biophysical data, soil, imagery, and fruit composition. The standardised and aggregated samples from four vineyards over three seasons were included in the estimation of ‘common variograms’ to assess how this technique could aid growers in producing geostatistically rigorous maps of fruit composition variability without cumbersome, single season sampling efforts.

Vine diseases have a strong impact on vineyards sustainability, which in turns leads to strong economic consequences. Among those diseases, Flavescence dorée spreads quickly and is incurable, which led in France to the setup of a mandatory pest control implying the systematic use of pesticides and the prospection and uprooting of every infected plants. Remote sensing could be a very powerful tool to optimize prospection as it allows to produce quickly accurate maps over large areas. Recent studies have shown that high spatial resolution (10cm/pixel) multispectral images acquired from UAVs allow to map Flavescence dorée in vineyards using leaves discolorations [e.g. Albetis et al., Remote Sensing, 2017].

Since the emergence of phylloxera, grafting has been the most used propagation method in viticulture. Despite all the improvement measures implemented in the nurseries, it is frequent that graft success rates vary depending on the nursery process and scion/rootstock combinations. The reasons behind this unsatisfactory behaviour are still unknown and can be diverse, although carbohydrate reserves might be hypothesised to be crucial, since callus, root, and new tissue formation will be built based on them. In order to identify the effect of carbohydrates on grafting success, nine combinations were established based on the starch content in grapevine scionwoods (cv. Tempranillo clone VN69) and rootstocks cuttings (110 Richter clone 237) used for grafting: Low (L), Medium (M), High (H).

Irrigation is an important practice to influence vine quality, especially in Mediterranean regions, characterized by hot summers and severe droughts during the growing season. This study focused on deficit irrigation regime influence on amino acids composition of Monastrell grapevines under semiarid conditions (Albacete, Southeastern of Spain). In 2019, two treatments were applied: non-irrigation (NI) and regulated deficit irrigation (RDI), watered at 30% of the estimated crop evapotranspiration from fruit set to onset of veraison. Grape amino acids content was analyzed by HPLC. Berries from non-irrigated vines showed higher concentration of several amino acids, such as tryptophan (73%), arginine (70%), lysine (36%), isoleucine (27%), and leucine (21%), compared to RDI grapes. Arginine is, together with ammonium ion, the principal nitrogen source for yeasts during the alcoholic fermentation; while isoleucine, tryptophan, and leucine are precursors of fermentative volatile compounds, key compounds for wine quality. Moreover, NI treatment increased in a 14% the total amino acids content in grapes compared to RDI treatment. The reported effects might be because yield was 70% higher in RDI vines than in the NI ones and, therefore, the sink demand was increased in the irrigated vines. In addition, NI vines suffered more severe water stress and it is known that the amino acids synthesis and accumulation can be influenced by the plant response to stress. According to the results, the irrigation regime showed effect on amino acids concentration in Monastrell grapes under semiarid conditions. Grapes from non-irrigated vines showed a higher content of several amino acids relevant to the fermentative process and to the wine aroma compounds formation. It is demonstrated that the final content of nitrogen-related components in grapes is influenced by the irrigation regime. The convenience of the irrigation strategy to suggest will depend on the desired wine style and the target yield levels.