Proposition of a simplified approach of the viticultural landscape

Extensive studies have been conducted on grapevine responses to water deficit, but these responses are difficult to generalise since numerous factors can influence the response(s), including genotype, developmental stage, soil, climate, and season.

Pomace and grape stems are the main solid organic waste from winery industries, resulting from the pressing and/or fermentation processes it is generated in large amounts in many parts of the world

Marlborough Sauvignon Blanc has rapidly gained an international reputation for style and quality. The extent to which this can be attributed to the climate, soils or vineyard management is at present unclear. However, the young alluvial soils of the Wairau Plains are considered to play an important role in determining this unique wine style. Marked changes in soil texture occur on the Wairau Plains over short distances.

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.

Sauvignon blanc is the most important variety in cool valleys in central Chile accounting 15,522 ha which corresponds to 42.4% of the cultivated surface with white varieties in Chile