Similarities among wine aromas and landscape scents around the vineyard in five Mediterranean sites

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.

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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 project VINIoT pursues the creation of a new technological vineyard monitoring service, which will allow companies in the wine sector in the SUDOE space to monitor plantations in real time and remotely at various levels of precision. The system is based on spectral images and an IoT architecture that allows assessing parameters of interest viticulture and the collection of data at a precise scale (level of grape, plant, plot or vineyard) will be designed. In France, three subjects were specifically developed: evaluation of maturity, of water stress, and detection of flavescence dorée. For the evaluation of maturity, it has been decided first to work at the berry scale in the laboratory, then at the bunch scale and finally in the vineyard. The acquisition of the spectral hyperstal image as well as the reference analyzes to measure the maturity, were carried out in the laboratory after harvesting the berries in a maturity monitoring context. This work focuses on a case study to predict sugar content of three different grape varieties: Syrah, Fer Servadou and Mauzac. A robust method called Roboost-PLSR, developed in the framework of this work (Courand et al., 2022), to improve prediction model performance was applied on spectra after the acquirement of hyperspectral images. Regarding the evaluation of water stress, to work with a significant variability in terms of water status, it has been worked first with potted plants under 2 different water regimes. The facilities have allowed the supervision of irrigation and micro-climatic conditions. The regression models on agronomic variables (stomatal conductance, water potential, …) are studied. To detect flavescence dorée, the experimental plan has consisted of work at leaf scale in the laboratory first, and then in the field. To detect the disease from hyper-spectral imaging, a combination of multivariate curve resolution-alternating least squares (MCR-ALS) and factorial discriminant analysis (FDA) was proposed. This strategy proved the potential towards the discrimination of healthy and infected leaves by flavescence dorée based on the use of hyperspectral images (Mas Garcia et al., 2021).

Water is the main limiting factor for yield in viticulture. Improving drought adaptation in viticulture will be an increasingly important issue under climate change. Genetic variability of water deficit responses in grapevine partly results from the rootstocks, making them an attractive and relevant mean to achieve adaptation without changing the scion genotype. The objective of this work was to characterize the rootstock effect on the diurnal regulation of scion transpiration. A large panel of 55 commercial genotypes were grafted onto Cabernet Sauvignon. Three biological repetitions per genotype were analyzed. Potted plants were phenotyped on a greenhouse balance platform capable of assessing real-time water use and maintaining a targeted water deficit intensity. After a 10 days well-watered baseline period, an increasing water deficit was applied for 10 days, followed by a stable water deficit stress for 7 days. Pruning weight, root and aerial dry weight and transpiration were recorded and the experiment was repeated during two years. Transpiration efficiency (ratio between aerial biomass and transpiration) was calculated and δ13C was measured in leaves for the baseline and stable water deficit periods. A large genetic variability was observed within the panel. The rootstock had a significant impact on nocturnal transpiration which was also strongly and positively correlated with maximum daytime transpiration. The correlations with growth and water use efficiency related traits will be discussed. Transpiration data were also related with VPD and soil water content demonstrating the influence of environmental conditions on transpiration. These results highlighted the role of the rootstock in modulating water deficit responses and give insights for rootstock breeding programs aimed at identifying drought tolerant rootstocks. It was also helpful to better define the mechanisms on which the drought tolerance in grapevine rootstocks is based on.