DNA-Free genome editing confers disease resistance in grapevine

One of the most important effects of climate change in wine-growing areas is the advance of phenological stages, especially concerning early berry ripening. In the hottest seasons, this results in a lack of synchrony between sugar and phenolic ripeness. In order to cope with this fact, a general effort is being made by researchers and growers aiming at delaying ripening through different strategies. One of the proposed approaches is the application of elicitors. This study aims to assess the effect at the transcriptomic level of the application of three hormone- and natural-based elicitors in Tempranillo.

Les approches du terroir en tant qu’entité géographique (zonages) connaissent un développement accru récent en lien avec l’essor des SIG. Les méthodes, les objectifs et les critères utilisés varient considérablement selon les études.

Water and heat stress impose new challenges to irrigation management in the Mediterranean areas. This reality has a major impact on the vineyard ecosystem, particularly on the scarce water resources of the Alentejo region (South Portugal). To mitigate this problem, irrigation management should focus on optimizing yield and fruit quality per volume of water applied. This work aims to discuss the use of predawn leaf water potential and soil water status relationships as a decision tool for irrigation management taking as basis data from a field trial where two deficit irrigation strategies were compared.

Water deficit is one of the most important effects of climate change able to affect agricultural sectors. In general, it determines a reduction in biomass production, and for some plants, as in the case of grapevine, it can endorse fruit quality. The monitoring and management of plant water stress in the vineyard

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.