Contribution of grape and oak wood barrels to pyrrole content in wines – Influence of several cooperage parameters

45 non irrigated vineyards distributed in the DO (Denomination) Pla i Llevant de Mallorca and the DO Binissalem Mallorca were used to investigate the characteristics of production and quality and their relationships certain environmental factors and cultural practices. The grape varieties investigated are autochthonous to the island of Mallorca, Manto Negro and Callet as red and Prensal Blanc as white. All plants were measured for four consecutive years in the main production and quality parameters. Among the environmental factors, the type of soil has been studied, more specifically its water retention capacity, the planting density, the age of the vineyard and the level of viral infection. The presence or absence of virus seems to have no effect on any component studied in the varieties studied. For the white variety Prensal Blanc age is negatively correlated with production and the number of bunches, nevertheless it does not cause any effect on the required quality parameters. However, for the red varieties Callet and Manto Negro, the age of the plantation is the variable that best correlates with the quality parameters, therefore the old vines should be the object of preservation by the viticulturists and winemakers in order to guarantee its contribution to the quality of the wines made with these varieties.

With the aim of producing premium wines, it is admitted that moderate environmental stresses may contribute to the accumulation of compounds of interest in grapes. However the ongoing climate change, with the appearance of more limiting conditions of production is a major concern for the wine industry economic. Will it be possible to maintain the vineyards in place, to preserve the current grape varieties and how should we anticipate the adaptation measures to ensure the sustainability of vineyards? In this context, the question of the responses and adaptation of grapevine to abiotic stresses becomes a major scientific issue to tackle. An abiotic stress can be defined as the effect of a specific factor of the physico-chemical environment of the plants (temperature, availability of water and minerals, light, etc.) which reduces growth, and for a crop such as the vine, the yield, the composition of the fruits and the sustainability of the plants. Water stress is in many minds, but a systemic vision is essential for at least two reasons. The first reason is that in natural environments, a single factor is rarely limiting, and plants have to deal with a combination of constraints, as for example heat and drought, both in time and at a given time. The second reason is that plants, including grapevine, have central mechanisms of stress responses, as redox regulatory pathways, that play an important role in adaptation and survival. Here we will review the most recent studies dealing with this issue to provide a better understanding of the grapevine responses to a combination of environmental constraints and of the underlying regulatory pathways, which may be very helpful to design more adapted solutions to cope with climate change.

This study assessed the suitability of grapevine growing in three DOs (Empordà, Pla de Bages and Penedès) of Catalonia (NE Spain) over the 21st century. For this purpose, an estimation of water needs and agroclimatic and phenological indicators was made. Climate change impacts were estimated at 1 km pixel resolution using temperature and precipitation projections from several general circulation models (GCM) and two climate change scenarios: RCP 4.5 (stabilization scenario) and RCP 8.5 (worst-case scenario). Potential crop evapotranspiration (following FAO procedure) and a daily water balance considering soil water holding capacity were used to estimate actual evapotranspiration of vines and, finally, water needs. Dynamics would be similar in the three DOs studied although the magnitude of impact differs. Water needs would be 2 and 3 times greater (ranging from 0 to more than 1500 m3/ha) than current water needs at both climate change scenarios. Moreover, blooming date would advance from 3 to 6 weeks, harvest date from 1 to 2.5 months, resulting in growing cycles from 10 to 80 days shorter. It should also be noted that frost risk would decrease from 6 to 76%, the number of days with temperatures above 30ºC during ripening would rise from 48 to 500% and tropical nights (minimum temperature >20ºC) at ripening would increase from 28 to 150%, depending on the scenario and the DOs. The impacts of climate change in the three DOs could result in significant limitations for grapevine cultivation and wine production if adaptive strategies are not applied. This result could serve as a basis for the design of specific and particular adaptation strategies to improve and maintain vineyards in the DOs studied and could be extrapolated to similar DOs and regions.

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.

Grapevine yield is a key indicator to assess the impacts of climate change and the relevance of adaptation strategies in a vineyard landscape. At this scale, a yield model should use a number of parameters and input data in relation to the information available and be able to reproduce vineyard management decisions (e.g. soil and canopy management, irrigation). In this study, we used data from six experimental sites in Southern France (cv. Syrah) to calibrate a model of grapevine yield limited by water constraint (GraY). Each yield component (bud fertility, number of berries per bunch, berry weight) was calculated as a function of the soil water availability simulated by the WaLIS water balance model at critical phenological phases. The model was then evaluated in 10 grapegrowers’ plots, covering a diversity of biophysical and technical contexts (soil type, canopy size, irrigation, cover crop). We identified three critical periods for yield formation: after flowering on the previous year for the number of bunches and berries, around pre-veraison and post-veraison of the same year for mean berry weight. Yields were simulated with a model efficiency (EF) of 0.62 (NRMSE = 0.28). Bud fertility and number of berries per bunch were more accurately simulated (EF = 0.90 and 0.77, NRMSE = 0.06 and 0.10, respectively) than berry weight (EF = -0.31, NRMSE = 0.17). Model efficiency on the on-farm plots reached 0.71 (NRMSE = 0.37) simulating yields from 1 to 8 kg/plant. The GraY model is an original model estimating grapevine yield evolution on the basis of water availability under future climatic conditions.  It allows to evaluate the effects of various adaptation levers such as planting density, cover crop management, fruit/leaf ratio, shading and irrigation, in various production contexts.