Physiological and growth reaction of Shiraz/101-14 Mgt to row orientation and soil water status

Diverse ripening disorders affect grapevine resulting in high economic losses worldwide. The common obvious symptom is shriveling berries, however the shriveling pattern and the consequences for berry quality traits are distinct in each disorder. Among them, the disorder berry shrivel is characterized by a reduced sugar accumulation short after the onset of berry ripening leaving the clusters unsuitable for wine processing. Although our knowledge on BS increased recently, potential internal or external triggers contributing to the induction of BS are yet to be explored.

Terroir is a complex concept which associates soil, climate, grape variety and cultural practices that include the training system and oenological techniques. It is a type of social construction with man at its centre. The typicality of a wine is also a social construction which is the result of an agreement among specialists vis à vis a given quality of the wine whose references are the wine’s origins (e.g. terroir) and taste.

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.

Current remote sensing strategies rely heavily on reflectance data and energy balance modelling using thermal imagery to estimate crop water use and stress. These approaches show great promise for driving precision management decisions, but still require work to better understand how detected changes relate to meaningful physiological changes. Under water stress, grapevines exhibit a range of responses involving both biological and physical changes within leaves and canopies.

Flavonoids, including flavonols, anthocyanins, and tannins, are
important contributors to grape and wine quality, and their biosynthesis is strongly influenced by bunch microclimate. While the synergistic effect of light and temperature has been intensively examined on flavonoids in relation to bunch exposure, studies targeting the sole effect of high temperature have mostly
focused on anthocyanins during the ripening period. With tannin biosynthesis starting around flowering, heatwaves occurring earlier in the grape growing season could be critical. Only a few papers report the impact of temperature on tannin synthesis and accumulation; to date, none have examined the effect of high temperature extremes which, in the context of climate change, relates to increases in heatwave intensity.