Biochemical characterization of grape skin cell wall during ripening in relation to Botrytis cinerea susceptibility of two Champagne cultivars

In the context of global warming, water scarcity is becoming an increasing issue worldwide. However, the reference method to characterize vine water deficit is based on water potential measurement, which is a destructive and discontinuous method. The current climatic context emphasizes the need for more precise and more continuous vineyard water use measurements in order to optimize irrigation and vine water deficit monitoring.

The wine industry faces the consumer’s increasing demand for a sustainable and environmentally-friendly production [1]. This demand has been shared and boosted by the European Union within the European Green Deal in the Farm to Fork strategy that aims to reduce a 50% the pesticide utilisation in farming systems. Among the agronomical approaches so far proposed, the use of mould resitant hybrid varieties -based on crossings of Vitis vinifera with other Vitis spp [2]- with a high tolerance to the attack of vine patogens is gaining the vinegrowers attention and the production area is continuously increasing

Context and purpose of the study. Vitis vinifera grapevine is a perennial crop which is globally cultivated, surviving cold winters in temperate zones by entering a state of dormancy.

Over the last years, the potential use of non-Saccharomyces yeasts to modulate the production of target metabolites of oenological interest has been well recognized. Among non-Saccharomyces yeasts, Starmerella bacillaris (synonym Candida zemplinina) is considered one of the most promising species to satisfy modern market and consumers preferences due to its peculiar characteristic (enhance glycerol and total acidity contents and reduce ethanol production). Mixed fermentations using Starm. bacillaris and Saccharomyces cerevisiae starter cultures represent a way to modulate metabolites of enological interest, taking advantage of the phenotypic specificities of the former and the ability of the latter to complete the alcoholic fermentation. However, the consumption of nutrients by these species and their produced metabolites may inhibit or stimulate the growth (and malolactic activity) of lactic acid bacteria (LAB).

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.