Use of computational modelling for selecting adsorbents for improved fining of wine

“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.

Grape by-products (including skins, seeds, stems and vine shoots) are rich in health promoting polyphenols. Their extraction from winery waste and their following purification are of special interest to produce extracts with high added value compounds. Meanwhile, the growing concern over environmental problems associated with economic constraints, require the development of environmentally sustainable extraction technologies. The extraction using semi-continuous subcritical water, as a natural solvent at high temperature and high pressure a technology is promising “green” technology that is environmentally friendly, energy efficient and improve the extraction process in plant tissues.

Consumers predominantly use visual, aromatic and texture cues as quality/preference indicators to describe olfactory sensations. In this study, the effect of micro-organism in wine production was investigated using analytical and sensory techniques to achieve relevant analytical characterisation. Selected anthocyanins, flavan-3-ols, flavonols and phenolic acids were quantified in Syrah wines using RP-HPLC-DAD. Standard oenological parameters were also measured. Syrah grape must was fermented with various combinations of Saccharomyces cerevisiae (S. cerevisiae) and non-Saccharomyces (Metschnikowia pulcherrima or Hanseniaspora uvarum) yeasts, which was followed by sequential inoculation of lactic acid bacteria (LAB) (Oenococcus oeni or Lactobacillus plantarum).

Contribution Foam is the characteristic that differentiates sparkling wines from still wines, being the first sensory attribute that tasters and consumers perceive and that determines the final quality of sparkling wines [1]. The foaming properties mainly depend on the chemical composition of wines [2-3], and different factors involved in wine composition will have an effect on foam quality. In Spain, the sparkling wine market focuses on the production of white and rosé sparkling wine, with very low production of red sparkling wines. However, this type of wines is elaborated in countries like Australia, South-Africa, Argentina, Italy or Portugal, with a great acceptance by consumers. No studies on the foaming characteristics of red sparkling wines have been found.

Leaf removal in the bunch zone is a common viticultural practice with several objectives, yet it has been difficult to conclusively link the physiological mechanism(s) and metabolic berry impact to this widely practiced treatment. We used a field-omics approach1 in a Sauvignon blanc high altitude model vineyard, showing that the early leaf removal in the bunch zone caused quantifiable and stable responses (over years) in the microclimate where the main perturbation was increased exposure. We provide an explanation for how leaf removal leads to the shifts in grape metabolites typically linked to this treatment and confirm anecdotal evidence and previous reports that leaf removal treatment at an early stage of berry development affects “quality-associated” metabolites (monoterpenes and norisoprenoids).