Studio per la caratterizzazione delle produzioni vitivinicole dell’area del Barbera d’Asti DOC

Botrytis cinerea Pers., the causal agent of grey mould disease, is responsible for substantial economic losses, as it causes reduction of grape and wine quality and quantity. Exploitation of antagonistic yeasts is a promising strategy for controlling grey mould incidence and limiting the usage of synthetic fungicides. In our previous studies, 119 different indigenous yeasts were screened for putative multidimensional modes of action against filamentous fungus B. cinerea [1]. The most promissing biocontrol yeast was Pichia guilliermondii ZIM624, which exhibited several anatagonistic traits (production of cell wall degrading enzymes, chitinase and β-1,3-glucanase; demonstration of in vitro inhibitory effect on B. cinerea mycelia radial growth; production of antifungal volatiles, assimilation of a broad diversity of carbon sources, contributing to its competitivnes in inhabiting grapes in nature).

The main goal of the current study is the development of a cost-effective and easy-to-use method suitable for use in the laboratory of commercial wineries to analyze wine aroma. Additionally, this study attempted to establish a prediction model for wine quality gradings based on their aroma, which could reveal the important aroma compounds that correlate well with different grades of perceived quality METHODS: Parameters of the SHS−GC−IMS instrument were first optimized to acquire the most desirable chromatographic resolution and signal intensities. Method stability was then exhibited by repeatability and reproducibility. Subsequently, compound identification was conducted. After method development, a total of 143 end-ferment wine samples of three different quality gradings from vintage 2020 were analyzed with the SHS−GC−IMS instrument. Six machine learning methods were employed to process the results and construct a quality prediction model. Techniques that aim to explain the model to extract useful insights were also applied.

Melatonin is a bioactive compound with antioxidant properties, that has been found in many fermented beverages, such as beer and wine [1]. Indeed, it has been shown that yeast can synthesize melatonin during alcoholic fermentation, although its role inside the cell, as well as the metabolic pathway involved in its synthesis, is still unclear [1]. Recent studies showed that during fermentation, melatonin interacts with different proteins of the glycolytic pathway in both Saccharomyces and non-Saccharomyces yeast, for instance glyceraldehyde 3-phosphate dehydrogenase, pyruvate kinase or enolase [2].

In California vineyards, irrigation is considered as one of the most important decisions growers will make. Recent research has revealed that decisions of when to begin irrigation and how much water to apply have considerable consequences for final grape quality and hence wine quality. However, it is unclear whether and to what extent the average winegrape grower uses objective data to begin irrigating or to determine the amount of water to apply.

Recycled organic mulch within the row in vineyard floor management has become an interesting ecological strategy to adapt the crop to climate change consequences in semi-arid regions.
This study aimed to assess the impact of three recycled organic mulches [straw (STR), grape pruning debris (GPD), and spent mushroom compost (SMC)] and two conventional soil management practices [herbicide (HERB) and under-row tillage (TILL)] on vegetative vigour (NDVI), production (kg/plant), and physiological parameters (δ13C in grapes and leaf gas exchange during four grapevine phenology stages). Additionally, temperature and water soil parameters were collected at three soil depths. Data was collected during the 2021 and 2022 grapevine growing seasons in La Rioja, Spain.