Analysis of the oenological potentials of different oak forests in Hungary

Must clarification is an important step occurring just after grape extraction in the elaboration of white wine, consisting in a solid-liquid separation. Traditionally, low must turbidity, around 50-150 NTU, is generally reached in white winemaking in order to prevent reductive aromas and facilitating alcoholic fermentation. Alternatively, a higher turbidity (300 NTU or above) can be sought for reasons such as a better expression of grapes identity (terroir), or for getting a must matrix that could supposedly lead to wines having greater ageing potential.

Bioactive polyphenols from grapes and wines, like stilbenes and flavonols (SaF), are often determined to nutritional evaluation, but also for many other purposes. The objective of this study was to quantify SaF in red wines from “Campanha Gaúcha”, a large and young viticultural region from South Brazil. Moreover, through statistical analysis, evaluate the influence of these compounds according to varieties, production process, harvest years and micro-regions of cultivation. A total of 58 samples of red wines were analyzed by high-performance liquid chromatography coupled to diode array detector (HPLC-DAD) for determination of trans-resveratrol (R), quercetin (Q), myricetin (M), kaempferol (K), trans-e-viniferin (V) and their precursor, cinnamic acid (C).

Despite the extensive research performed during the last decades, the multifactorial mechanism responsible for the white wine protein haze formation is not fully characterized. Herein, a new model is proposed, which is based on the experimental identification of sulfur dioxide as a major modulating factor inducing wine protein haze upon heating. As opposed to other reducing agents, such as 2-mercaptoethanol, dithiothreitol and tris(2-carboxyethyl)phosphine hydrochloride (TCEP), the addition of SO2 to must/wine upon heating cleaves intraprotein disulfide bonds, hinders thiol-disulfide exchange during protein interactions and can lead to the formation of novel inter/intraprotein disulfide bonds. Those are eventually responsible for wine protein aggregation which follows a nucleation-growth kinetic model as shown by dynamic light scattering [1].

The present work contributes by developing a rapid sensory-directed methodology for the screening and selection of high quality wines with different sensory profiles Therefore, Verdejo and Tempranillo musts were fermented with 50 different yeasts each under controlled laboratory conditions. Resulting samples were firstly categorized according to five levels of quality by a panel of wine professionals (Sáenz-Navajas, Ballester et al. 2013). Higher quality samples were described by flash profiling by a semi-trained panel
(Valentin, Chollet et al. 2012) and most distinctive samples were screened by gas chromatography-olfactometry (GC-O) (López, Aznar et al. 2002).

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.