Different yield regulation strategies in semi-minimal-pruned hedge (SMPH) and impact on bunch architecture

There is a growing trend on the transition from conventional to agroecological management of vineyards. However, the impact of practices, such as reduced-tillage, organic fertilization and cover crops, is not well-understood regarding the soil microbial diversity, and its relationship with the soil physicochemical properties in the subsurface depth near the rooting zone. Soil bacterial diversity is an important contributor towards plant health, productivity and response to environmental stresses. A field experiment was conducted by sampling subsurface soil bacterial community (NGS and qPCR) near to the root zone of Macabeu and Xarel·lo vineyards, located at the Penedes. 3 organic (ECO) and 3 conventional (CON) vineyards, with more than 10 years of respective management were sampled (n=5 each plot). ECO practices did not affect bacterial and fungal abundance but increased significantly the ammonium oxidizing bacteria and alpha-diversity (Inv.Simpson). Interestingly beta-diversity was significantly affected by the management strategy. ANOSIM-tests revealed a significative effect of the management (ecological vs conventional) and plot, on the soil microbial structure (ASV abundance). Main phyla depicted were Proteobacteria, Actinobacteria and Acidobacteria, whose relative abundances were not affected by the management. EdgeR assay revealed a significant increase of Cyanobacteria and decrease of Gemmatimonadetes and Firmicutes phyla in ECO. Interestingly, the grapevine variety was not correlated with the soil microbial community structure. Mantel-test revealed an important correlation (Spearman) of some physicochemical parameters with the soil microbiota structure, in order of importance: texture, EC, pH Ca/Mg, Mg/P, K+, Mg2+, Ca2+, SO42-, and OM. N-NH4 and NTK, which were higher in the ECO managed soils, did not correlated significantly with the soil microbiome population. The results revealed the importance of combining a deep physicochemical characterization of each replicate with the microbial diversity assessment to gain better insights on the relationship between soil microbiome and vineyard management.

Protected Designation of Origin “Jumilla” (PDO Jumilla) is located in the Spanish provinces of Albacete and Murcia, in the South-eastern part of the Iberian Peninsula, where most of the models predict a severe impact of climate change in next decades. PDO Jumilla covers an area of 247,054 hectares, of which more than 22,000 hectares

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.

Increasingly warm and dry climate conditions are challenging the viticulture and winemaking sector. Digital technologies and crop modelling bear the promise to provide practical answers to those challenges. As viticultural activities strongly depend on harvest date, its early prediction is particularly important, since the success of winemaking practices largely depends upon this key event, which should be based on an accurate and advanced plan of the annual cycle. Herein, we demonstrate the creation of modelling tools to assess grape ripeness, through sugar concentration monitoring. The study area, the Portuguese Côa valley wine region, represents an important terroir in the “Douro Superior” subregion. Two varieties (cv. Touriga Nacional and Touriga Franca) grown in five locations across the Côa Region were considered. Sugar accumulation in grapes, with concentrations between 170 and 230 g l-1, was used from 2014 to 2020 as an indicator of technological maturity conditioned by meteorological factors. The climatic time series were retrieved from the EU Copernicus Service, while sugar data were collected by a non-profit organization, ADVID, and by Sogrape, a leading wine company. The software for calibrating and validating this model framework was the Phenology Modeling Platform (PMP), version 5.5, using Sigmoid and growing degree-day (GDD) models for predictions. The performance was assessed through two metrics: Roots Mean Square Error (RMSE) and efficiency coefficient (EFF), while validation was undertaken using leave-one-out cross-validation. Our findings demonstrate that sugar content is mainly dependent on temperature and air humidity. The models achieved a performance of 0.65

Excessive fertilization of the vineyard leads to low quality grapes, increased costs and a negative impact on the environment. In order to establish an integrated management system aimed at a sustainable fertilization of the vineyards, nutritional reference levels were established. For this purpose, 30 representative vineyards of the Albariño variety were studied, in which soil and petiole analyses were carried out for two years and grape yield and quality at harvest were measured. In both years of study, soil pH, calcium, sodium and cation exchange capacity were positively correlated with calcium content and negatively correlated with manganese in grapes. Irrigated vineyards had higher levels of aluminium in soil and lower levels of calcium in petiole. Climatic conditions were very different in the years of the study. The year 2019 was colder than usual, in 2020 there was a marked water stress with high summer temperatures. This resulted in medium-high acidity in grapes in 2019 and low acidity in 2020, with sugar levels being similar both years. A very marked decrease in must amino nitrogen was observed in 2020, with ammonia nitrogen remaining stable. The correlation of acidity and sugar values in grapes with soil and petiole analysis data made it possible to establish reference levels for the nutritional diagnosis of the Albariño variety in this region. Based on these results, an easy-to-use TIC application is currently being created for grapegrowers, aimed at improving the sustainability of the vineyard through reasoned fertilization. This study has now been extended to other Galician vine varieties.