Soil survey and chemical parameters evaluation in viticultural zoning

The grape variety Gewürztraminer is known to be affected by two physiological disorders namely berry shrivel and bunch stem necrosis. During the season 2014 we noticed a new symptomatology type of ripening disorder on the variety. The new symptom showed not all berries fallowing the normal maturation stages, but single berries remaining at a soft but green stage till harvest. The broad distribution of these so called “green berries” symptoms in different production sites of our region, caused huge damage due to the difficulty of eliminating single berries per bunch before harvesting. Therefore, the Research Centre Laimburg began to investigate the reasons and origins of this new symptom. This work shows the results of first attempts to find causes for the symptom as well as the resulting approach to mitigate symptoms. Applications of magnesium leaf fertilizer showed first promising results against this putative disorder. To study the causal effect of the green berries 30 symptomatic vineyards in 2014 have been selected for a monitoring during the season 2016. To evaluate the foliar nutrient treatment two vineyards have been selected for application of magnesium sulfate and magnesium chloride. Leaf and berry nutrient analysis, as well as the main quality parameters during ripening have been performed. As soon as “green berries” symptoms appeared, incidence and severity have been evaluated. Most of the symptomatic vineyards of the 2016 monitoring showed light to clear magnesium deficit symptoms on their foliage. Only during the seasons 2020 and 2021 “green berries” symptoms could be found in the leaf fertilizer treatment vineyards. Both seasons showed a significant effect of the magnesium treatments to reduce the incidence and severity of the symptom. It seems that the appearance of the “green berries” symptom on Gewürztraminer is correlated to a disturbed uptake of magnesium of the vines.

Terroir is not only a geographical site, but it is a more complex concept able to express the “collective knowledge of the interactions” between the environment and the vines mediated through human action and “providing distinctive characteristics” to the final product (OIV 2010). It is often treated and accepted as a “black box”, in which the relationships between wine and its origin have not been clearly explained. Nevertheless, it is well known that terroir expression is strongly dependent on the physical environment, and in particular on the interaction between soil-plant and atmosphere system, which influences the grapevine responses, grapes composition and wine quality. The Terroir studying and mapping are based on viticultural zoning procedures, obtained with different levels of know-how, at different spatial and temporal scales, empiricism and complexity in the description of involved bio-physical processes, and integrating or not the multidisciplinary nature of the terroir. The scientific understanding of the mechanisms ruling both the vineyard variability and the quality of grapes is one of the most important scientific focuses of terroir research. In fact, this know-how is crucial for supporting the analysis of climate change impacts on terroir resilience, identifying new promised lands for viticulture, and driving vineyard management toward a target oenological goal. In this contribution, an overview of the last findings in terroir studies and approaches will be shown with special attention to the terroir resilience analysis to climate change, facing the use and abuse of terroir concept and new technology able to support it and identifying the terroir zones.

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.

As elsewhere, southwestern France vineyards face more recurrent summer heat waves these last years. Among the possibilities of adaptation to this climate changing parameter, the use of net shading is a technique that allow for limiting canopy exposure to radiations. In this trial, we tested net shading installed on one face of the canopy, on a north-south row-oriented plot of cv. Gros Manseng trained on VSP system in the PDO Pacherenc-du-Vic-Bilh. The purpose was to characterize the effects on the ambient canopy temperatures and radiations during the season and to observe the consequences on the composition of grapes and wines. Two sorts of net were used with two levels of obstruction (50% and 75%) of the photosynthesis active radiation (PAR). They have been installed on the west side of the canopy and compared to a netless control. Temperature and PAR sensors registered hourly data during the season. On specific summer day (hot and sunny) manual measurements took also place on bunches (temperature) and in different spots of the canopy (PAR). The results showed that, on clear days, the radiation is lowered by the shade nets respecting the supplier criteria. The effects on the ambient canopy temperature were inconstant on this plot when we observed the data from the global period of shading between fruit set and harvest. However, during hot days (>30°C), the temperature in the canopy was reduced during afternoon and the temperature of the bunch surface was reduced as well comparing to the control. A decrease of the maturity parameters of the berries, sugar and acidity, was also observed. Concerning the wine aromatic potential, no differences clearly appeared.

A large varietal collection including over 1700 varieties was maintained in Conegliano, ITA, since the 1950s. Phenological data on a subset of 400 grape varieties including wine grapes, table grapes, and raisins were acquired at bud break, flowering, veraison, and ripening since 1964. Despite the efforts in maintaining and acquiring data over such an extensive collection, the data set has varying degrees of missing cases depending on the variety and the year. This is ubiquitous in phenology datasets with significant size and length. In this work, we evaluated four state-of-the-art methods to estimate missing values in this phenological series: k-Nearest Neighbour (kNN), Multivariate Imputation by Chained Equations (mice), MissForest, and Bidirectional Recurrent Imputation for Time Series (BRITS). For each phenological stage, we evaluated the performance of the methods in two ways. 1) On the full dataset, we randomly hold-out 10% of the true values for use as a test set and repeated the process 1000 times (Monte Carlo cross-validation). 2) On a reduced and almost complete subset of varieties, we varied the percentage of missing values from 10% to 70% by random deletion. In all cases, we evaluated the performance on the original values using normalized root mean squared error. For the full dataset we also obtained performance statistics by variety and by year. MissForest provided average errors of 17% (3 days) at budbreak, 14% (4 days) at flowering, 14.5% (7 days) at veraison, and 17% (3 days) at maturity. We completed the imputations of the Conegliano dataset, one of the world’s most extensive and varied phenological time series and a steppingstone for future climate change studies in grapes. The dataset is now ready for further analysis, and a rigorous evaluation of imputation errors is included.