Control of bacterial growth in carbonic maceration winemaking through yeast inoculation

The vital role of soils in supporting life on our planet cannot be overstated. Soils provide numerous ecosystem services and functions, including biomass production, carbon sequestration, physical support, biological habitat, and genetic reserve, among others. Understanding the characteristics and sensitivity of soils in a specific terroir, along with effective soil management practices, is crucial for the sustainable management of natural resources.

Vine cane extracts are a valuable byproduct due to their rich content of polyphenols, vitamins, and other beneficial compounds, which can affect and benefit the vine and the grapes. This study aims to evaluate the response of grapevine plants to irrigation with water supplemented with a vine cane extract, both at physiology response and phenolic composition in different parts of the plant (root, trunk, shoot, leaf, and berry).
Cane extract was obtained by macerating crushed pruning residues with warm water (5:1) and pectolytic enzymes. Two-year-old potted plants were irrigated with water (Control) while others were irrigated with cane extracts, either at 1:4 (w/v, cane extract/water; T 1:4) or at 1:8 (w/v, cane extract/water; T 1:8).

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.

The Mediterranean basin is one of the most vulnerable regions to Climate Change effects. According to unanimous forecasts, the vineyards of Castilla-La Mancha will be among the most adversely affected by rising temperatures and water scarcity during the vine’s vegetative period. One potential strategy to mitigate the negative impacts of these changes involves the identification of grapevine varieties with superior water use efficiency, while ensuring satisfactory yields and grape quality.

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).