Polyphenols in kombucha: Metabolomic analysis of biotransformations during fermentation

Obtaining high-quality RNA from grape tissues, including berry pulp, berry skins, stems, rachis, or roots, is challenging due to their composition, which includes polysaccharides, phenolic compounds, sugars, and organic acids that can negatively affect RNA extraction. For instance, polyphenols and other secondary metabolites can bind to RNA, making it difficult to extract a pure sample. Additionally, RNA can co-precipitate with polysaccharides, leading to lower extraction yield. Also, sugars and organic acids can interfere with the pH and ionic properties of the extraction buffer. To address these challenges, we optimized a protocol for RNA isolation from grape tissues.

Aims: The aims of this study were to i) characterize the impact of geographical origin and viticulture treatments on Chilean Cabernet-Sauvignon, and ii) develop machine learning models to predict its quality. 

In response to increasing societal demands for environmentally-friendly viticulture, winegrowers are adapting their cultivation techniques, particularly by reducing the use of herbicides.

Air temperature is the key driver of grapevine phenology and a significant environmental factor impacting yield and quality for a winegrape growing region. In this study the optimal downscaled CMIP5 ensemble for computing thegrowing season average temperature (GST) viticulture climate classification index was determined to spatially compute on a decadal basis predictions of the GST climate index and the grapevine sugar ripeness (GSR) model for Pinot Noir throughout the Willamette Valley (WV) American Viticultural Area (AVA). Forecasts for average temperature and a 220 g/L target sugar concentration level were computed using daily Localized Constructed Analogs (LOCA) downscaled CMIP5 historic and Representative Concentration Pathways (RCP) future climate projections of minimum and maximum daily temperature. We explore spatiotemporal trends of the GST climate classification index and Pinot Noir specific applications of the GSR phenology model for the WV AVA. Spatiotemporal computations of the GST climate index and Pinot Noir specific applications of the GSR model enable the opportunity to explore relationships between their computed values with one intent being to provide updated GST ranges that better align with current temperature-based modeling understanding of Pinot Noir grapevine phenology and the viticultural application of LOCA CMIP5 climate projections for the WV AVA. The Pinot Noir specific applications of the GSR model or the GST index with updated bounds indicate that the percent of the WV AVA area suitable for Pinot Noir production is currently at or near its peak value in the upper 80s to lower 90s of this century.

Wine storage ensuring the quality and correct aging is one of the issues that wineries, wine traders and consumers encounter after wine bottling.