Perception, liking and emotional response of tropical fruit aromas in Chardonnay wines

The plant rhizosphere microbial communities are an essential component of plant microbiota, which is crucial for sustaining the production of healthy crops. The main drivers of the composition of such communities are the growing environment and the planted genotype. Recent viticulture studies focus on understanding the effects of these factors on soil microbial composition since microbial biodiversity is an important determinant of plant phenotype, and of wine’s organoleptic properties. Microbial biodiversity of different wine regions, for instance, is an important determinant of wine terroir.

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.

The presence of acetic acid bacteria in wine can lead to the appearance of acetic acid at concentrations above the perception threshold, causing the wine rejection by the consumer. During the winemaking process, avoiding the presence of acetic acid bacteria is very difficult, as there is always a residual population accompanying the wine[1], and the problem arises with the significant development of these microorganisms that metabolizes large amounts of acetic acid.
The concern of wineries to control the presence of acetic acid bacteria in wines during their conservation is due to the absence of simple and effective analyses that allow the detection of these microorganisms in the initial stages.

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).

Grapevine varieties from South-America, commonly known as criollas, originated because of the natural crossbreeding of grapevine varieties brought by the Spaniards. The objective of this work was to evaluate the potential of some varieties to produce sparkling wines considering the effect of lees contact time. The following varieties were used: Moscatel Rosado, Criolla Chica, Pedro Gimenez, Blanca Oval, Canelón, and the European variety Chardonnay (control), planted in the ampelographic collection of EEA Mendoza INTA (Argentina). Pilot-scale vinifications were carried out to obtain the base wines, in 20 L glass containers. The second fermentation was performed through the traditional method.