Effect of Working Atmospheres on the Detection of Diacetyl by Resistive SnO2 Sensor

Nanostructured metal oxide semiconductors (MOS) are considered proper candidates to develop low cost and real-time resistive sensors able to detect volatile organic compounds (VOCs), e.g., diacetyl. Small quantities of diacetyl are generally produced during the fermentation and storage of many foods and beverages, conferring a typically butter-like aroma. Since high diacetyl concentrations are undesired, its monitoring is fundamental to identify and characterize the quality of products. In this work, a tin oxide sensor (SnO2) is used to detect gaseous diacetyl. The effect of different working atmospheres (air, N2 and CO2), as well as the contemporary presence of ethanol vapors, used to reproduce the typical alcoholic fermentation environment, are evaluated. SnO2 sensor is able to detect diacetyl in all the analyzed conditions, even when an anaerobic environment is considered, showing a detection limit lower than 0.01 mg/L and response/recovery times constantly less than 50 s.

Progresses in the production of ethanol from lignocellulosic biomass using Saccharomyces cerevisiae by fermentation engineering

Ethanol fermentation is a biological procedure which converts sugars such as glucose, fructose, and sucrose into cellular energy, producing ethanol and carbon dioxide as by-products. Since yeasts perform this conversion in the absence of oxygen, alcoholic fermentation is generally considered to be an anaerobic process. Ethanol fermentation has many uses, including the production of alcoholic beverages, the production of ethanol fuel, and bread making. The increasing demand for biofuels around the globe has also prompted the necessity to seek other means to meet the demands. In this review, the general ideologies, methodologies, general chemistry and biochemistry and conditions of the production of ethanol by fermentation engineering using Saccharomyces cerevisiae are highlighted. The quest to reduce pressure on staple foods has necessitated the attention now given to the use of lignocellulose biomass, despite the complexity of the process. It concludes by suggesting ways to improve yield and commercialization of the use of lignocellulosic biomass for ethanol fermentation.

Wine Yeasts 1.0

The conversion of grape juice into wine is a complex biochemical process involving alcoholic fermentation, production of wide range of metabolites and interactions of yeast strains, bacteria and fungi [...]

Technological innovation in the winery addressing oenology 4.0: Testing of an automated system for the alcoholic fermentation management

In recent years, the use of automated machine tools in the wine industry has increasingly gained ground to simplify and optimize winemaking, complying with Industry 4.0 requirements. This work aimed to analyse a system for the automatic management of yeast nutrition in alcoholic fermentation in terms of environmental, management, and economic performance in comparison with traditional fermentation management. The automated system is a transportable and easily installable place and start system, equipped with a control unit and rods for the dosage of nutrients, and it works with a memory unit in which fermentative kinetics curves are loaded. The curves are predefined or customized according to oenologists’ needs. Hence, fermentation time, manpower, nutrients, oxygen, water, and energy consumption were evaluated concerning the alcoholic fermentation process. The analysis was carried out considering two different Italian wineries with different working capacities. Furthermore, life cycle assessment methodology and variable costs analysis was performed. Overall, the automated system reveals to be a promising investment, especially if applied to wineries characterized by high-volume tanks, where scale factor played a crucial role. Nutrients used by the automated system are more expensive but more environmentally sustainable than traditional ones.

Study of the Yeast Strain Influence and the Alcoholic Fermentation Conditions on the Higher Alcohols and Aldehydes Content in Gamza Wines

The influence of temperature and inoculum amount of yeast culture on the ability of the strains Saccharomyces cerevisiae Badachoni and Saccharomyces cerevisiae 24-6 to synthesize higher alcohols and aldehydes was studied. Yeast showed the highest fermentation activity at a temperature of 28oC. Neural networks had been applied and mathematical models were derived, describing with high accuracy the experimental data on the change of the total amount of higher alcohols and aldehydes in the fermentation process depending on the conditions. The higher alcohols ratio had increased during the process. The Badachoni strain revealed better ability to synthesize the studied metabolite as compared to the 24-6 strain. The Badachoni had produced the greatest amount of higher alcohols when the process occurred at 28°C, whereas the 24-6 at 24oC. The aldehydes synthesis had reached its peak during the rapid fermentation, thereafter it began to go down. The studied yeast synthesized more aldehydes when the process took place at a lower temperature. For both strains the maximum was observed under the conditions 20oС/4%. The analysis of the obtained wines had confirmed that quantitatively Badachoni produced more total higher alcohols and the 24-6 more total aldehydes. In both strains within one temperature range, in all variants, with increasing the inoculum amount of yeast culture the studied metabolites ratio went up too.

Medium chain fatty acids and fatty acid esters as potential markers of alcoholic fermentation of white wines

Aroma components of wines play an important role in the sensory quality of wines. In our paper we investigate the effect of commercially available yeast nutrients under different fermentation parameters. Caproic acid, caprylic acid, capric acid, and different fatty acid esters were used as markers of the alcoholic fermentation process. The optimal temperature for the fermentation of different white wines was at 15–16 °C, in the case of examined wines lower concentrations of fatty acids and fatty acid esters were found at this temperature. At 25–26 °C fermentation temperature very high concentrations of fatty acids and fatty acid esters were detected. Applying different nitrogen-containing wine additives we managed to achieve better aroma profiles for white wines even using musts of lower quality.

Alcoholic Fermentation Monitoring and pH Prediction in Red and White Wine by Combining Spontaneous Raman Spectroscopy and Machine Learning Algorithms

In the following study, total sugar concentrations before and during alcoholic fermentation, as well as ethanol concentrations and pH levels after fermentation, of red and white wine grapes were successfully predicted using Raman spectroscopy. Fluorescing compounds such as anthocyanins and pigmented phenolics found in red wine present one of the primary limitations of enological analysis using Raman spectroscopy. Unlike the spontaneous Raman effect, fluorescence is a highly efficient process and consequently emits a much stronger signal than spontaneous Raman scattering. For this reason, many enological applications of Raman spectroscopy are impractical as the more subtle Raman spectrum of any red wine sample is in large part masked by fluorescing compounds present in the wine. This work employs a simple extraction method to mitigate fluorescence in finished red wines. Ethanol and total sugars (fructose plus glucose) of wines made from red (Cabernet Sauvignon) and white (Chardonnay, Sauvignon Blanc, and Gruner Veltliner) varieties were modeled using support vector regression (SVR), partial least squares regression (PLSR) and Ridge regression (RR). The results, which compared the predicted to measured total sugar concentrations before and during fermentation, were excellent (R2SVR = 0.96, R2PLSR = 0.95, R2RR = 0.95, RMSESVR = 1.59, RMSEPLSR = 1.57, RMSERR = 1.57), as were the ethanol and pH predictions for finished wines after phenolic stripping with polyvinylpolypyrrolidone (R2SVR = 0.98, R2PLSR = 0.99, R2RR = 0.99, RMSESVR = 0.23, RMSEPLSR = 0.21, RMSERR = 0.23). The results suggest that Raman spectroscopy is a viable tool for rapid and trustworthy fermentation monitoring.