Performance of Selected Uruguayan Native Yeasts for Tannat Wine Production at Pilot Scale

Wine flavour is the integration of distinct physiologically defined sensory systems that combine taste, aroma and trigeminal sensations, and it is a key determinant factor for the acceptance of wine by consumers. Volatile compounds, are important contributors to wine flavour, specially to aroma. These small and low-boiling point compounds are easily released into the air allowing to enter and move within the nasal or oral cavities where they can bind the olfactory receptors. Additionally, wine also contains aroma precursors, which are non-volatile compounds, but that can be broken down releasing volatile odorants. During wine tasting, all these chemicals (volatiles and non-volatiles) can be submitted to the action of salivary enzymes.

Less and less chemical plant protection products are approved by the E U. Plant pathogenic fungi become increasingly resistant to the active ingredients that have been around for a long time. Besides, there is a valid demand for effective products that can be applied in organic cultivation.
We examined Metschnikowia strains under laboratory conditions in order to find effective strains against B. cinerea. The antimicrobial mechanism of these yeasts is based on the competition for the ferric ions from the environment. Metschnikowia cells release the pulcherriminic acid which chelates with Fe3+, forming the pigment pulcherrimin.

By dissecting the root system architecture (RSA) into its underpinning components (e.g. root emission, axial growth, radial growth, branching, root direction or tropism) and identifying the relationships between them, functional-structural 3D root models are promising tools for analyzing the diversity and complexity of root system phenotypes with Genotype × Environment interactions. The model parameters are assumed to be synthetic traits, less influenced by the environment, and consequently with less polygenic architectures than the integrative RSA traits they drive. Root models can serve as a basis for in silico development of root system ideotypes by highlighting the developmental processes and parameters that most likely influence RSA fitness.

In the production of sparkling wines, during the second fermentation, mannoproteins are released by yeast autolysis, which affect the quality of the wines. The effect of mannoproteins has been extensively studied, and may affect aroma and foam quality. However, there are no studies on the effect of other polysaccharides such as those from grapes. Considering the large production of waste from the wine industry, it was proposed to obtain polysaccharide-rich extracts from some of these by-products[1].

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).