Unravel the underlying mechanisms of delaying ripening techniques in grapevine

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.

The foliar application of urea has been shown to be able to satisfy the specific nutritional needs of the vine as well as to increase the nitrogen composition of the must. On the other hand, the use of nanotechnology could be of great interest in viticulture as it would help to slow down the release of urea and protect it against possible degradation. Several studies indicate that cell wall synthesis and remodeling are affected by nitrogen availability.

In recent years characterized by hot dry summers, the implementation of innovative irrigation tools in the vineyard represents a crucial challenge to ensure optimal production and to avoid excess of water consumption. It is known that the grapevine reacts to multiple stresses – i.e., high temperatures and wa- ter shortage – through adaptive mechanisms that are detrimental to the yield. Furthermore, this condi- tion is usually aggravated by high solar radiation, which could negatively affect the phenolic composi- tion of the grapes. Therefore, a cooling system has been developed aiming to reduce bunches’ sunburn damage.

Australia is the seventh largest producer of wine and crushed 1.42 million tonnes of wine grapes in the 2001 vintage.

Temperature is a relevant parameter during vineyard development, affecting vine phenology and grape maturity. Moreover, the climate of the different Chilean valleys influences the varieties cultivated, the ripening period and the final quality of the wines. The use of growing degree days (GDD) is known worldwide for the study of climate in viticulture regions. However, little is known about the evolution of maturity and the sugar loading stop, based on this parameter.