Aromatic characterization of Moscato Giallo by GC-MS/MS and stable isotopic ratio analysis of the major volatile compounds

Wine is one of the most representative components of Mediterranean diet. Moderate wine intake together with food, has been positively correlated with reduced risk of many chronic diseases. This beneficial effect seems to be ascribed to elevated polyphenolic content of wine [1]. Traditional approaches for the identification of wine biomarkers consumption include targeted metabolomics that focuses on the quantification of well-defined metabolites, losing a valuable information about a massive number of compounds. On the other hand, untargeted metabolomics can disclose a large quantity of signals corresponding to potential biomarkers in a single analysis with high sensitivity and resolution.

Since the mid-1980s, several surveys have been carried out in La Rioja to search for populations of the sylvestris grapevine subspecies (Vitis vinifera L. subsp. sylvestris Gmelin). The banks of the Ebro River and its tributaries (Alhama, Cidacos, Leza, Iregua, Najerilla, Oja and Tirón rivers), as well as the surrounding vegetation of their valleys have been covered. So far, all the populations found are alluvial, forming part of the riparian vegetation of the Najerilla (the first reported population in La Rioja [1]), Iregua, and the vicinity of Oja valleys.

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).

Soil is important in the carbon cycle and the dynamics of greenhouse gases (CO2, CH4 and N2O). Key soil characteristics, such as organic matter content, texture, structure, pH and microbial activity, play a determining role in GHG emissions[1]. The objective of the study is to delimit different types of soil, with different soil management and to be able to verify the differences in CO2, CH4 and N2O emissions. The study was carried out in a vineyard of Bodegas Campo Viejo in Logroño (La Rioja), whose plant material is Vitis vinifera L. cv. Tempranillo.

Trichoderma is one of the most widely used fungal biocontrol agents on vineyards due to its multiple benefits on this crop, such as its fungicidal and growth promoting capacity. In this work, we have analyzed the effect on the concentration of nutrients in grapevine leaves and on the quality of the grape must after spraying an autochthonous strain of Trichoderma harzianum and one of the main secondary metabolites produced by this genus, 6-pentyl-α-pyrone (6PP).