Use of a new, miniaturized, low-cost spectral sensor to estimate and map the vineyard water status from a mobile 

Climate change and harvest date decisions have led to the evolution of must quality over the last decades. Increases in must sugar concentrations are among the most obvious consequences, quantitatively. Saccharomyces cerevisiae is a robust and acid tolerant organism. These properties, its sugar to ethanol conversion rate and ethanol tolerance make it the ideal production organism for wine fermentations. Unfortunately, high sugar concentrations may affect S. cerevisiae and lead to growth inhibition or yeast lysis, and cause sluggish or stuck fermentations. Even sublethal conditions cause a hyperosmotic stress response in S. cerevisiae which leads to increased formation of fermentation by-products, including acetic acid, which may exceed legal limits in some wines.

Grapes from warm(ing) climates often contain excessive sugars but lack acidity. This can lead to highly alcoholic wines with compromised stability and balance. The yeast Lachancea thermotolerans can ameliorate such wines due to its metabolic peculiarity – partial fermentation of sugars to lactic acid. This study aimed to elucidate the population-wide diversity in L. thermotolerans, whilst selecting superior strains for wine sector. An extensive collection of isolates (~200) sourced from different habitats worldwide was first genotyped on 14 microsatellite loci. This revealed differentiation of L. thermotolerans genetic groups based on the isolation substrate and geography. The 94 genotyped strains were then characterised in Vitis vinifera cv. Chardonnay fermentations.

Volatile sulphur compounds are a group of impact odorants with low odour thresholds that can contribute both positively and negatively to wine aroma. The varietal thiols, 3MH and 3MHA, are known to contribute positive tropical aromas to white wines and are most abundant in Sauvignon Blanc wines. The group of compounds contributing negative aromas are known as reductive sulphur compounds (RSCs) as they add a reductive aroma of asparagus, cooked vegetables and rotten egg to wines. All these compounds play a part in and are a result of the sulphur pathway in the yeast cell during fermentation and therefore attempting to increase the concentration of the varietal thiols may directly influence the concentration of the RSCs. The varietal thiols and the low molecular weight RSCs are highly volatile and therefore their sensory perception can change rapidly over time.

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.

Increasingly warm and dry climate conditions are challenging the viticulture and winemaking sector. Digital technologies and crop modelling bear the promise to provide practical answers to those challenges. As viticultural activities strongly depend on harvest date, its early prediction is particularly important, since the success of winemaking practices largely depends upon this key event, which should be based on an accurate and advanced plan of the annual cycle. Herein, we demonstrate the creation of modelling tools to assess grape ripeness, through sugar concentration monitoring. The study area, the Portuguese Côa valley wine region, represents an important terroir in the “Douro Superior” subregion. Two varieties (cv. Touriga Nacional and Touriga Franca) grown in five locations across the Côa Region were considered. Sugar accumulation in grapes, with concentrations between 170 and 230 g l-1, was used from 2014 to 2020 as an indicator of technological maturity conditioned by meteorological factors. The climatic time series were retrieved from the EU Copernicus Service, while sugar data were collected by a non-profit organization, ADVID, and by Sogrape, a leading wine company. The software for calibrating and validating this model framework was the Phenology Modeling Platform (PMP), version 5.5, using Sigmoid and growing degree-day (GDD) models for predictions. The performance was assessed through two metrics: Roots Mean Square Error (RMSE) and efficiency coefficient (EFF), while validation was undertaken using leave-one-out cross-validation. Our findings demonstrate that sugar content is mainly dependent on temperature and air humidity. The models achieved a performance of 0.65