Entomopathogenic nematodes application for controlling Lobesia botrana in grapevine and their impact on grapevine quality 

The O2 uptake in the different winemaking processes is generally considered to be negative for the sensory characteristics of white and rosé wines. Wine racking is a critical point of O2 uptake, as the large surface area of the wine exposed during this operation and the inability to maintain an effective inert gas blanket over it.
The objective was to study O2 uptake during the racking of a model wine without using inert gases and to compare it with the purging of the destination tank with different inert gases.

The increasingly frequent heat waves during grape ripening pose challenges for premium wine grape production. This makes the development of irrigation and canopy management techniques of great importance to maximize yield and grape quality. A field experiment was carried out during 2021 and 2022 using Manto negro wine grapes to study the effect of two irrigation strategies and different light exposure levels on grape quality.

The study conducted various fermentations of different grape juices using various strains of Lachancea thermotolerans and one strain of Saccharomyces cerevisiae. Because of the new conditions caused by climate change, wine acidity must be influenced as well as the volatile profile. Non-Saccharomyces yeasts such as L. thermotolerans are real options to mitigate the impact of climate change in wine production.

Crops are facing increasing biotic and abiotic stress pressures due to global changes. However, trade-off mechanisms between these stresses and the underlying physiological processes are still poorly understood, especially in perennial crop species. To better understand these trade-offs, we studied the effect of drought on grapevine (Vitis vinifera) physiology and esca-related wood fungal communities. Esca is a vascular disease caused by a community of wood-infecting pathogenic fungi, and characterized by trunk necrosis, leaf scorch symptoms, yield losses, and mortality.

The main objective of the work was to develop a simple, robust and selective analytical tool that allows predicting the authenticity of Tempranillo wines from DOCa Rioja. The techniques of voltammetry and absorbance-transmission and fluorescence excitation emission matrix (A-TEEM) spectroscopy have been applied in combination with machine learning (ML) algorithms to classify red wines from DOCa Rioja according to region (Alavesa, Alta or Oriental) and category (young, crianza or reserva).