Accumulation of polyphenols in Barbera and Nebbiolo leaves during the vegetative season

Inactive dry yeast treatments in the vineyard are a tool used with the aim to improve the concentration and quality of secondary metabolites in grapes, leading to a better differentiation of the wines made from grapes differently treated. In this work, a foliar spraying treatment with yeast derivatives specifically designed to be used with the patent pending application technology of Lallemand Inc. Canada (LalVigne® Mature, Lallemand Inc., Montreal, Canada) was tested on Vitis vinifera L. cv. Barbera and Nebbiolo black winegrapes. The aim was to evaluate the effect of this treatment on the phenolic compounds accumulation, the skin physical-mechanical properties and the related phenolic extractability. Prior to analysis, the berries were sorted by flotation in order to evaluate their distribution by density class, and to determine the skin texture parameters of berries with different sugar contents, thus understanding also the ripening effect.

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.

Bacterial malolactic fermentation (MLF) has a considerable impact on wine quality. The yeast strain used for primary fermentation can consistently stimulate (MLF+ phenotype) or inhibit (MLF- phenotype) malolactic bacteria and the MLF process as a function of numerous winemaking practices, but the molecular evidence behind still remains a mystery. In this study, such evidence was elucidated by the direct comparison of extracellular metabolic profiles of MLF+ and MLF- yeast phenotypes. Untargeted metabolomics combining ultrahigh-resolution FT-ICR-MS analysis, powerful machine learning methods and a comprehensive wine metabolite database, discovered around 800 putative biomarkers and 2500 unknown masses involved in phenotypic distinction.

The interactions among aromatic compounds and proteins is an important issue for the quality of foods and beverages. In wine, the loss of flavor after vinification is associated to bentonite treatment and this effect can be the result of the removal of aroma compounds which are bound wine proteins. This phenomenon was recently demonstrated for long chain fatty acids and their ethyl esters (1). Since these latter compounds are spectroscopically silent, their association with proteins is not easy to measure.

Multiple Factor Analysis (MFA) According to the Chenin blanc Association of South Africa, there are three recognized dry wine styles, Fresh and Fruity (FF), Rich and Ripe Unwooded (RRU), and Rich and Ripe Wooded (RRW), classically attributed with the help of sensory evaluation. One of the “rapid methods” has drawn our attention for the purpose of simplifying and making style attribution for large sample sets, evaluated during different sessions, more robust. Polarized Projective Mapping (PPM) is a hybrid of Projective Mapping (PM) and Polarised Sensory Positioning (PSP). It is a reference-based method in which poles
(references) are used for the evaluation of similarities and dissimilarities between samples.