Studio dell’ambiente viticolo attraverso la parametrazione (punto di incrocio) delle curve di maturazione delle uve (pinot nero, oltrepo’ pavese pv italia settentrionale – 45° parallelo Nord)

A unique “terroir” can be found in southern Bolivia, which combines the specific features of climate, topography and altitude of high valleys, with the management of grapevines staked on trees. It is one of the rare remnants of agroforestry viticulture. A survey was carried out among 29 grapegrowers in three valleys, to characterize the structure and management of these vineyards, and identify the services they expect from trees. Farms were small (2.2 ha on average) and 85% of vineyards were less than 1 ha. Viticulture was associated with vegetable, fruit and fodder production, sometimes in the same fields. Molle trees were found in all plots, together with one or two other native tree species. Traditional grapevine varieties such as Negra Criolla, Moscatel de Alejandría and Vicchoqueña were grown with a large range of densities from 1550 to 9500 vines ha-1. From 18 to 30% of them were staked on trees, with 1.2 to 4.9 vines per tree. The management of these vineyards (irrigation, fertilization and grapevine protection) was described, the most particular technical operation being the coordinated pruning of trees and grapevines. Three types of management could be identified in the three valleys. Grapegrowers had a clear idea of the ecosystem services they expected from trees in their vineyards. The main one was protection against climate hazards (hail, frost, flood). Then they expected benefits in terms of pest and disease control, improvement of soil fertility and resulting yield. At last, some producers claimed that tree-staking was quicker and cheaper than conventional trellising. It can be hypothesized then that agroforestry is a promising technique for the agroecological transition of viticulture. Its contribution to the “terroir” of the high valleys of southern Bolivia and its link with the specificities of the wines and spirits produced there remain to be explored.

The study of climate is relevant as an element conditioning the typicity of a product, its quality and sustainability over the years. The grapevine development and growth and the final grape and wine composition are closely related to temperature, while climate components vary at mesoscale according to topography and/or proximity to large bodies of water. The objective of this work is to assess the mesoclimate of the Atlantic region of Uruguay and to determine the effect of topography and the ocean on temperature and consequently on Tannat grapevine behavior.

In viticulture, a warming climate can have a very significant impact on grapevine development and therefore on the quality and characteristics of wines across different spatial scales, ranging from global to local. In order to adapt wine-growing to climate change, global climate models can be used to define future scenarios, but only at the scale of major wine regions. Despite the huge progress made over the last ten years in terms of the spatial resolution of climate models (now downscaled to a few square kilometres), they are not yet sufficiently precise to account for the local climate variability associated with such parameters as local topography, in spite of these parameters being decisive for vine and wine characteristics. This study describes a method to downscale future climate scenarios to vineyard scale. Networks of data loggers have been used to collect air temperature at canopy level in the Waipara winegrowing region (New Zealand) over five growing seasons. These measurements allow the creation of fine-scale geostatistical models and maps of temperature (at 100 m resolution) for the growing season. In order to model climate change at pilot site scale, these geostatistical models have been combined with regional climate change predictions for the periods 2031-2050 and 2081-2100 based on the RCP8.5 climate change scenario. The integration of local climate variability with regionalized climate change simulations allows assessment of the impacts of climate change at the vineyard scale. The improved knowledge gained using this methodology results from the increased horizontal resolution that better addresses the concerns of winegrowers. The results provide the local winegrowers with information necessary to understand current processes, as well as historical and future viticulture trends at the scale of their site, thereby facilitating decisions about future response strategies.

The current climate changes are directly threatening the balance of the vineyard at harvest time. The maturation period of the grapes is shifted to the middle of the summer, at a time when radiation and air temperature are at their maximum. In this context, the implementation of corrective practices becomes problematic. Unfortunately, our knowledge of the climate effect on the quality of different grape varieties remains very incomplete to guide these choices. During the Innovine project, original experiments were carried out on Syrah to study the combined effects of normal or high air temperature and varying degrees of exposure of the berries to the sun. Berries subjected to these different conditions were sampled and analyzed throughout the maturation period. Several quality characteristics were determined, including anthocyanin content. The objective of the experiments was to investigate which climatic determinants were most important for anthocyanin accumulation in the berries. Temperature and irradiance data, observed over time with a very thin discretization step, are called functional data in statistics. We developed the procedure SpiceFP (Sparse and Structured Procedure to Identify Combined Effects of Functional Predictors) to explain the variations of a scalar response variable (a grape berry quality variable for example) by two or three functional predictors (as temperature and irradiance) in a context of joint influence of these predictors. Particular attention was paid to the interpretability of the results. Analysis of the data using SpiceFP identified a negative impact of morning combinations of low irradiance (lower than about 100 μmol m−2 s−1 or 45 μmol m−2 s−1 depending on the advanced-delayed state of the berries) and high temperature (higher than 25oC). A slight difference associated with overnight temperature occurred between these effects identified in the morning.

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.