NMR approach for monitoring the photo-degradation of riboflavin and methionine

Grapevine is grown as a graft since the end of the 19th century. Rootstocks not only provide tolerance to Phylloxera but also ensure the supply of water and mineral nutrients to the scion. Rootstocks are an important mean of adaptation to environmental conditions, because the scion controls the typical features of the grapes and wine. However, among the large diversity of rootstocks worldwide, few of them are commercially used in the vineyard. The aim of this study was to investigate the extent to which rootstocks modify the mineral composition of the petioles of the scion. Vitis vinifera cvs. Cabernet-Sauvignon, Pinot noir, Syrah and Ugni blanc were grafted onto 55 different rootstock genotypes and planted in a vineyard as three replicates of 5 vines. Petioles were collected in the cluster zone with 6 replicates per combination. Petiolar concentrations of 13 mineral elements (N, P, K, S, Mg, Ca, Na, B, Zn, Mn, Fe, Cu, Al) at veraison were determined. Scion, rootstock and the interaction explained the same proportion of the phenotypic variance for most mineral elements. Rootstock genotype showed a significant influence on the petiole mineral element composition. Rootstock effect explained from 7 % for Cu to 25 % for S of the variance. The difference of rootstock conferred mineral status is discussed in relation to vigor and fertility. Rootstocks were also genotyped with 23 microsatellite markers. Data were analysed according to genetic groups in order to determine whether the petiole mineral composition could be related to the genetic parentage of the rootstock. Thanks to a highly powerful design, it is the first time that such a large panel of rootstocks grafted with 4 scions has been studied. These results give the opportunity to better characterize the rootstocks and to enlarge the diversity used in the vineyard.

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Climate has a significant impact in the success of any agricultural system, with a direct influence on the crops suitability to a given region, interfering on yield and quality and also with the economic sustainability of the productive activity. In the Douro Demarcated Region (RDD), as in most regions of the Mediterranean climate, the scarce precipitation (33% has less than 600 mm per year), and your high variability, associated with high rates of evapotranspiration during the summer, is usually one of the fundamental factors that limit the grapevine development, as well as the production and quality of the harvest. Thus, facing the scenario in temperature changes for the next decades (1.5-2.5°C) and confirming the predictions of precipitation decreases and/or great variability in the occurrence of heat waves and intense rainfall, the consequences for slope stability in mountain viticulture and sustainability of all operations involved, are risks to be taken into account. In this way, a deepest and sustained knowledge regarding the adaptation measures to adverse environmental conditions is of a crucial importance, enabling a more efficient adaptation of plant growth conditions and the optimization of production and quality of the grapevines. The development of this work, carried out in two commercial vineyards, one located in Soutelo do Douro, São João da Pesqueira, Cima Corgo sub-region, and another located in Numão, Vila Nova de Foz Côa, Douro Superior sub-region, it seeks to establish a relationship between climatic elements and physiological, productive and qualitative parameters, as well as to evaluate the effectiveness of adaptation measures, including different types of deficit irrigation (2002-2019) and the application of shading nets (2019-2020) in the physiological, viticultural and oenological behavior in the Touriga Nacional and Moscatel Galego Branco varieties, respectively. The results showed that the application of deficit irrigation allowed to significantly reduce the impact of the adverse weather conditions at key moments in the development of the grapevine, particularly in the period immediately before veráison and maturation, reducing the negative effects on the physiological processes and productivity, without compromise the must quality parameters. On the other hand, the application of shading nets significantly reduced de leaves temperature, allowing to increase the water potential, stomatal conductance and photosynthetic rate of grapes, which was reflected in the yield increase in the 2nd year of the study. For the maturation indicators, higher levels of total acidity, malic acid and assimilable nitrogen were obtained. The last measure presents a huge potential, being essential to carry out more years of trials to obtain stronger conclusions in terms of production parameters, but also in characteristics as important as the grape ripening components and the organoleptic characteristics of wines.

The Barossa zone is arguably one of the most well-recognised wine producing regions in Australia and internationally; known mainly for the production of its distinct Shiraz wines. However, within the broad Barossa geographical delimitation, a variation in terroir can be perceived and is expressed as sensorial and chemical profile differences between wines. This study aimed to explore the sub-division classification across the Barossa region using chemical and sensory measurements. Shiraz grapes from 4 different vintages and different vineyards across the Barossa (2018, n = 69; 2019, n = 72; 2020, n = 79; 2021, n = 64) were harvested and made using a standardised small lot winemaking procedure. The analysis involved a sensory descriptive analysis with a highly trained panel and chemical measurement including basic chemistry (e.g. pH, TA, alcohol content, total SO2), phenolic composition, volatile compounds, metals, proline, and polysaccharides. The datasets were combined and analysed through an unsupervised, clustering analysis. Firstly, each vintage was considered separately to investigate any vintage to vintage variation. The datasets were then combined and analysed as a whole. The number of sub-divisions based on the measurements were identified and characterised with their sensory and chemical profile and some consistencies were seen between the vintages. Preliminary analysis of the sensory results showed that in most vintages, two major groups could be identified characterised with one group showing a fruit-forward profile and another displaying savoury and cooked vegetables characters. The exploration of distinct profiles arising from the Barossa wine producing region will provide producers with valuable information about the regional potential of their wine assisting with tools to increase their target market and reputation. This study will also provide a robust and comprehensive basis to determine the distinctive terroir characteristics which exist within the Barossa wine producing region.

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.