Analysis of peptide fraction from white wines

The use of multivariate statistics to correlate chemical data to spectral information seems as a valid alternative for the quantification of red wine phenolics. The advantages of these techniques include simplicity and cost effectiveness together with the limited time of analysis required. Although many
publications on this subject are nowadays available in the literature most of them only reported feasibility
studies. In this study 400 samples from thirteen fermentations including five different cultivars plus 150
wine samples from a varying number of vintages were submitted to spectrophotometric and chromatographic phenolic analysis.

“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.

Varietal Riesling aroma relies strongly on the formation and liberation of bound aroma compounds. Floral monoterpenes, green C6-alcohols, fruity C13-norisoprenoids and spicy volatile phenols are predominantly bound to disaccharides, which are produced and stored in the grape berry during berry maturation. Grape processing aims to extract maximum amount of the precursors from the berry skin to increase the potential for a strong varietal aroma in the wine. Subsequent yeast selection plays an important part in this process.

Introduction: Malolactic fermentation (MLF) is a common process in winemaking to reduce wine acidity, maintain microbial stability and modify wine aroma. However, successful MLF is often hampered by their sluggish or stuck activity of malolactic bacteria (MLB) which may be caused by nutrient deficiency, especially when MLB are inoculated after alcoholic fermentation (Alexandre et al., 2004; Lerm et al., 2010). Identification and characterization of essential nutrients and growth factors for MLB allows for production of highly efficient nutrient supplements for MLF.

Climate change and harvest date decisions have led to the evolution of must quality over the last decades. Increases in must sugar concentrations are among the most obvious consequences, quantitatively. Saccharomyces cerevisiae is a robust and acid tolerant organism. These properties, its sugar to ethanol conversion rate and ethanol tolerance make it the ideal production organism for wine fermentations. Unfortunately, high sugar concentrations may affect S. cerevisiae and lead to growth inhibition or yeast lysis, and cause sluggish or stuck fermentations. Even sublethal conditions cause a hyperosmotic stress response in S. cerevisiae which leads to increased formation of fermentation by-products, including acetic acid, which may exceed legal limits in some wines.