Estimation of chemical age of red wines with the use of Fourier transform infrared spectroscopy (FT-IR) and chemometrics

Polyphenols are present in a wide variety of plants and foods such as tea, cacao and grape1. An important sub-class of these compounds is the flavanols present in grapes and wines as monomers (e.g (+)-catechin or (-)-epicatechin), or polymers also called condensed tannins or proanthocyanidins. They have important antioxidant properties2 but their biosynthesis remains partly unknown. Some recent studies have focused on the role of glycosylated intermediates that are involved in the transport of the monomers and may serve as precursors in the polymerization mechanism3, 4. The global objective of this work is to identify flavanol glycosides in grapes or wines, describe their structure and determine their abundance during grape development and in wine.

Fermentative aromas (especially esters and higher alcohols) highly impact the organoleptic profile of young and white wines. The production of these volatile compounds depends mainly on temperature and Yeast Available Nitrogen (YAN) content in the must. Available dynamic models predict the main reaction
(bioconversion of sugar into ethanol and CO2 production) but none of them considers the production kinetics of fermentative aroma compounds during the process of fermentation. We determined the production kinetics of the main esters and higher alcohols for different values of initial YAN content and temperature, using an innovative online monitoring Gas Chromatography device.

Saccharomyces cerevisiae (SC) is the main driver of alcoholic fermentation however, in wine, non-Saccharomyces species can have a powerful effect on aroma and flavor formation. This study aimed to compare untargeted volatile compound profiles from SPME-GC×GC-TOF-MS of Sauvignon blanc and Shiraz wine inoculated with six different non-Saccharomyces yeasts followed by SC. Torulaspora delbrueckii (TD), Lachancea thermotolerans (LT), Pichia kluyveri (PK) and Metschnikowia pulcherrima (MP) were commercial starter strains, while Candida zemplinina (CZ) and Kazachstania aerobia (KA), were isolated from wine grape environments. Each fermentation produced a distinct chemical profile that was unique for both grape musts. The SC-monoculture and CZ-SC sequential fermentations were the most distinctly different in the Sauvignon blanc while the LT-SC sequential fermentations were the most different from the control in the Shiraz fermentations.

Laboratório de Análisis del Aroma y Enologia (LAAE). Department of Analytical Chemistry, Faculty of Sciences, Universidad de Zaragoza, 50009, Zaragoza, Spain, During alcoholic fermentation, fusel (or Strecker) aldehydes are intermediates in the amino acid catabolism to form fusel alcohols following the Ehrlich Pathway (1). One of the main enzymes involved in this pathway is Alcohol Dehydrogenase (ADH), whose activity is highly strain dependent and determines the rate of conversion of aldehydes into fusel alcohols (2). This enzyme has a Zn2+ catalytic binding site, which suggests that the must Zn2+ levels will most likely influence the rate of reduction of aldehydes into alcohols. On the other hand, SO2 is commonly used in winemaking for its antiseptic and antioxidant properties.

Not only vintner’s decisions in the vineyard, but also winemaker’s choices of technology approaches in the cellar play a significant role in the final wine style and quality. Whereas traditional technologies within chosen terroir are quite well explored and thus somehow predictable, there is no proper knowledge available on possible outcomes in case of implementing novel, alternative winemaking strategies. To reveal their effects on wine aroma compounds and sensory characteristics, two alternative strategies
(cryoextraction or addition of whole grape berries during last stages of fermentation) were compared to classical Vipava valley winemaking approach as normally used for an autochthonous variety Zelen. After separate vinification and bottling, all the experimental wines were subjected to semiquantitative metabolic profiling of volatile compounds (VOCs) by means of GC/MS and were then also sensorialy evaluated by pre-trained panel.