An infrared laser sensor to characterize the gaseous headspace of champagne glasses under static and swirling conditions

Age-related macular degeneration (AMD) that is the main cause of visual impairment and blindness in Europe which is characterized by damages in the central part of the retina, the macula. This degenerative disease of the retina is mainly due to the molecular mechanism involving the production and secretion of vascular endothelial growth factor (VEF). Despite therapeutic advances thanks

This study present a detailed analysis of the rainfall and temperature changes in the Penedès region in the period 1995/ 96 – 2008/09, in comparison with the trends observed during the last 50 years, and its implications on phenology and yield.

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.

Forest fires in the vicinity of vineyards have significantly increased in the last decade and are a concern for grapegrowers and winemakers in many wine producing countries. The fires cause smoke drift throughout vineyards which cannot be avoided and may result in the production of wines described as ‘smoke tainted’. Such wines are characterized by undesirable sensory characters described as ‘smoky’, ‘burnt’, ‘ash’ aromas and flavours, and also may cause a lingering, unpleasant ashy aftertaste [1; 2].

The identification and management of intra-vineyard variability are key to precision viticulture, and sensors have been proven to be highly efficient tools for detecting these variations.