Exogenous dsRNA applications to identify novel candidate susceptibility genes to downy mildew

The aim of this work was the identification and quantification of polyphenols present in natural precipitate of a Sauvignon wine. Phenol analysis in wine precipitate was based on acid hydrolysis, CG- MS after derivatization, and LC-MS.

One of the main problems in viticultural production in Istria (Croatia) is a labour shortage in periods of intensive works, mainly during summer, respectively during tourist season.

Recent developments in satellite technology have yielded a substantial volume of data, providing a foundation for various machine learning approaches. These applications, utilizing extensive datasets, offer valuable insights into Earth’s conditions. Examples include climate change analysis, risk and damage assessment, water quality evaluation, and crop monitoring. Our study focuses on exploiting satellite thermal and multispectral imaging, and vegetation indexes, such as NDVI, in conjunction with ground truth information about soil type, land usage (forest, urban, crop cultivation), and irrigation water sources in the Trentino region in North-East of Italy.

Premium red wines are often aged in oak barrel. This widespread winemaking process is used, among others, to provide roundness and complexity to the wine. The study of wine evolution during barrel aging is crucial to better ensure control of wine quality.
¹H-NMR has already been proved to be an efficient tool to monitor winemaking process [1]. Indeed, it is a non-destructive technique, it requires a small amount of sample and a short time of analysis, yet it provides clues about several chemical families.

Polyphenols are common in human diets, primarily in plant-derived food and beverages. They influence multiple sensory properties such as aroma, flavour, colour, and taste, such as astringency and bitterness [1]. The major phenolic compounds in grapes and wines are anthocyanins and tannins (proanthocyanidins or condensed tannins).