Evaluating South African Chenin blanc wine styles using an LC-MS screening method

The use of next-generation sequencing (NGS) has helped understand microbial genetics in oenology. Current studies mainly focus on barcoded amplicon NGS but not shotgun sequencing, which is useful for functional analyses. Since the high percentage of grapevine DNA conceals the microbial DNA in must, the majority of sequencing data is wasted in bioinformatic analyses. Here we present capture depletion of grapevine whole genome DNA.

Malolactic fermentation (MLF) is a secondary step in the vinification process and it follows alcoholic fermentation (AF) which is predominantly carried out by Saccharomyces cerevisiae. These two processes result in the degradation of metabolites to produce secondary metabolites which also contribute to the final wine flavour and quality. AF results in the production of ethanol and carbon dioxide from sugars and MLF stems from the degradation of L-malic acid (a dicarboxylic acid) to L-lactic acid (a monocarboxylic acid). The latter process results in a smoother texture as the acidity of the wine is reduced by the process, it also adds to the flavour complexity of the wine.

In Enology the conventional processes of filtration for clarification and stabilization are giving place to alternative membrane processes, including nanofiltration (NF). Furthermore, the increased alcohol content in wines recorded in recent years became an important issue for all the main wine producing countries. Among techniques available to the wine industry to reduce the ethanol content, NF is certainly one of the newest. This study is focused on the evaluation of NF influence on wine physical-chemical composition, including mineral content, which in accordance to our best knowledge is a novelty.

During red wine ageing or conservation, color and taste change and astringency tends to reduce. These changes result from reactions of flavan-3-ols and/or anthocyanins among which condensation reactions with acetaldehyde are particularly important. The full characterization of these reactions has not been fully achieved because of difficulties in extracting and separating the newly formed compounds directly from wine. Model solutions mimicking food products constitute a simplified medium for their exploration, allowing the detection of the newly formed compounds, their isolation, and their structure elucidation.

“The Human being has an excellent ability to detect and discriminate odors but typically has great difficulty in identifying specific odorants”(1). Furthermore, “from a cognitive point of view the mechanism used to judge wines is closer to pattern recognition than descriptive analysis.” Therefore, when one wants to reveal the volatile “wine-like feature” pattern recognition techniques are required. Sensomics is one of the most recent “omics”, i.e. a holistic perspective of a complex system, which deals with the description of substances originated from microorganism metabolism that are “active” to human senses (2). Depicting the relevant volatile fraction in wines has been an ongoing task in recent decades to which several research groups have allocated important resources. The most common strategy has been the “target approach” in order to identify the “key odorants” for a given wine varietal.