Full automation of oenological fermentations and its application to the processing of must containing high sugar or acetic acid concentrations

Wine is a solution containing abundant volatile compounds which contribute to their aroma. Many of them are produced by yeast as metabolism by-products. Different yeast strains produce different volatile profiles. The possibility of studying the evolution of volatile compounds during fermentation, using sampling methods that not alter the volume of fermentation media, is of great interest. In spite of this, non-invasive methods to monitoring the evolution of volatile profile during fermentation have been seldom used. The goals of this work were to use by first time the headspace sorptive extraction (HSSE) as non-invasive method to monitor the evolution of volatile profiles throughout alcoholic fermentation and to study the changes on volatile profiles produced by Saccharomyces cerevisiae and Lachancea thermotolerans during fermentation of a must with high sugar content.

One of the key factors of the economical development of viticulture and wine industry in specific limited areas is the exploitation of ancient, local grape varieties. Therefore, in recent years the growing interest to rediscover minor varieties, previously cultivated, has promoted many studies. With this regard, the focus of this study was the Vitis vinifera L. cultivar Moscato nero d’Acqui, nowadays found only in old vineyards in the Acqui zone (North-West Italy). In particular, the aims of this work were: i) to investigate secondary metabolites profile of the grapes, and ii) to evaluate the attitude to the production of special wines.

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].

A method of suspect screening analysis to study grape metabolomics, was developed [1]. By performing ultra-high performance liquid chromatography (UHPLC) – high-resolution mass spectrometry (HRMS) analysis of the grape extract, averaging 320-450 putative grape compounds are identified which include mainly polyphenols. Identification of metabolites is performed by a new HRMS-database of putative grape and wine compounds expressly constructed (GrapeMetabolomics) which currently includes around 1,100 entries.

In general, there is a well-established lexicon related to wine aroma and taste properties; however mouth-feel-related vocabulary usually includes heterogeneous, multimodal and personalized terms. Gawel et al.
(2000) published a wheel related to mouthfeel properties of red wine. However, its use in scientific publications has been limited. The authors accepted that the approach had certain limitations as it included redundant and terms with hedonic tone and some others were absent. It is of high interest to generate a mouth-feel lexicon and finding the chemical compound or group of compounds responsible for such properties in red wine. In the present work a chemical fractionation method has been developed.