Climate variability and its effects in the Penedès vineyard region (NE Spain)

Infection of the grapes with Botrytis cinerea has a tremendous impact on the resulting crop yield and quality. Well-known problems that are associated with B. cinerea are specific off-flavors, poor filterability, and brownish color in white wines. The development of a B. cinerea infection strongly depends on weather conditions and is highly variable through different vintages. Typical control measures include defoliation and the use of fungicides, which involves high personnel and material costs. They also involve a great risk, especially since the effectiveness and time point of these treatments are difficult to predict.

Precision nutrient management in viticulture can be addressed on the basis of a spatial characterization of within‐vineyard vine

Protecting table grape vineyards with white hail‐nets is a common practice in Southern Italy. Hail‐nets result in shading effects of 10‐20 %, depending on their density

During bottle aging, many thiol compounds are involved in the expression of bouquet of great aged red wines according to the quality of the closure.1,2 Identifying thiol compounds in red wines is a challenging task due several drawbacks including, the complexity of the matrix, the low concentration of these impact compounds and the amount of wine needed.3,4
This work aims to develop a new strategy based on the functionalisation of oak wood organic extracts with H₂S, to produce new thiols, in order to mimic what can happen in red wine during bottle aging. Following this approach and through sensory analysis experiments, we demonstrated that the vanilla-like aroma of fresh oak wood was transformed into intense “meaty” nuances similar to those found in old but non oxidized red wines.

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).