Structural composition of polymeric polyphenols of red wine after long-term ageing: effect of vinification technology

In recent years, developing more efficient and sustainable viticulture management has been essential due to the impact of climate change in semiarid regions. For this reason, the use of recycled organic mulching (ROM) in the vineyard has become an interesting strategy to cope with water stress, isolated soil from extreme temperatures and improving soil humidity, control the presence of weeds and therefore reduce the inputs of herbicides and improve soil fertility. This work aimed to analyse the effect of three different organic mulches [straw (S), grape pruning debris (GPD) and spent mushroom compost (SMC)] and two traditional soil management techniques [herbicide (H) and interrow (IN)] on weed coverage and the spontaneous plant communities’ presence. Data sampling was collected throughout the vine vegetative cycle of 2021 in La Rioja, Spain. The different soil management techniques had a clear effect on weed coverage and his development during the vine vegetative cycle. SMC and H were the treatments with the highest and the lowest coverage percentage, respectively. IN had a delayed weed emergence at the beginning of the vine vegetative cycle, but finally it reached maximum values nearby SMC. GPD and S had similar effects on weed emergence, reaching 25-30% of the maximum coverage values. A total of 29 herbaceous species were identified during the vegetative cycle, some of them very isolated and occasional. Principal component analysis (PCAs) showed a good association between spontaneous species and treatments, furthermore, specific species-treatment associations were found. Moreover, three clear groups of herbaceous communities were identified by cluster analysis. This study provides interesting information about the effect of different alternative soil management on herbaceous plant coverage and weed species communities which could contribute to making more sustainable viticulture.

The objective of the work described here is the elaboration of a map of the different types of vineyard soils that to guide the famers in the choice of the most productive vine rootstocks and varieties. 90 vineyard soils profiles were analysed in the entire territory of the Origen Denominations of Valdepeñas. The sampling was carried out in 2018 (June to October) by making a sampling grid, followed by photointerpretation and control in the field. The studied soils can be grouped into 9 different soil types (according to FAO 2006 classification): Leptosols, Regosols, Fluvisols, Gleysols, Cambisols, Calcisols, Luvisols and Anthrosols. A map showing the soil distribution with different type of soils has been made with the ArcGIS program. Regarding to the choice of rootstock, Calcisoles are soils with a high active limestone content, so the rootstocks used in these soils must be resistant to this parameter; Luvisols are deep soils with high clay content, so they will support vigorous rootstocks. Because the cartographic units are composed of two or more subgroups, with are associated in variable proportions, 9 different soil associations have been established; Unit 1: Leptosols, Cambisols and Luvisols (80%, 15% and 5% respectively); Unit 2: Cambisols with Regosols and Luvisols (40%, 30% and 30% respectively); Unit 3: Cambisols and Gleysols with Regosols (40%, 40% and 20% respectively); Unit 4: Regosols with Cambisols, Leptosols and Calcisols (40%, 30%, 15% and 15% respectively); Unit 5: Cambisols, Leptosols, Calcisols and Regosols (25% each of them); Unit 6: Luvisols with Cambisol and Calcisols (80%, 10% and 10% respectively); Unit 7: Luvisols and Calcisols with Cambisols (40%, 40% and 20% respectively); Unit 8: Calcisols with, Cambisols and Luvisols (80%, 10% and 10% respectively); Unit 9: Anthrosols. These study allow to elaborate the first map of vineyard soils of this Protected Designation of Origin in Castilla-La Mancha.

Globalisation and climate change have radically transformed world wine production upsetting the established order of wine ecologies. Ecological risks and the future of traditional agricultural systems are widely debated in anthropology, but very little is understood of the particular challenges posed by climate change to viticulture which is seen by many as the canary in the coalmine of global agriculture. Moreover, wine as a globalised embedded commodity provides a particularly telling example for the study of climate change having already attracted early scientific attention. Studies of climate change in viticulture have focused primarily on the production of systematic models of adaptation and vulnerability, while the human and cultural factors, which are key to adaptation and sustainable futures, are largely missing. Climate experts have been unanimous in recognising the urgent need for a better understanding of the complex dynamics that shape how climate change is experienced and responded to by human systems. Yet this call has not yet been addressed. Climate ethnography, coined by the anthropologist Susan Crate (2011), aims to bridge this growing disjuncture between climate science and everyday life through the exploration of the social meaning of climate change. It seeks to investigate the confrontation of its social salience in different locations and under different environmental guises (Goodman 2018: 340). By understanding how wine producers make sense of the world (and the environment) and act in it, it proposes to focus on the co-production of interdisciplinary knowledge by identifying and foreshadowing problems (Goodman 2018: 342; Goodman & Marshall 2018). It seeks to offer an original, transformative and contrasted perspective to climate change scenarios by investigating human agency -individual or collective- in all its social, political and cultural diversity. An anthropological approach founded on detailed ethnographies of wine production is ideally placed to address economic, social and cultural disruptions caused by the emergence of these new environmental challenges. Indeed, the community of experts in environmental change have recently called for research that will encompass the human dimension and for more broad-based, integrated through interdisciplinarity, useful knowledge (Castree & al 2014). My paper seeks to engage with climate ethnography and discuss what it brings to the study of wine environmental futures while exploring the limitations of the anthropological environmental approach.

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.

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.