fermentation rate
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Author(s):  
David Henriques ◽  
Eva Balsa-Canto

The yeast Saccharomyces cerevisiae is an essential microorganism in food biotechnology; particularly, in wine and beer making. During wine fermentation, yeasts transform sugars present in the grape juice into ethanol and carbon dioxide. The process occurs in batch conditions and is, for the most part, an anaerobic process. Previous studies linked limited-nitrogen conditions with problematic fermentations, with negative consequences for the performance of the process and the quality of the final product. It is, therefore, of the highest interest to anticipate such problems through mathematical models. Here we propose a model to explain fermentations under nitrogen-limited anaerobic conditions. We separated the biomass formation into two phases: growth and carbohydrate accumulation. Growth was modelled using the well-known Monod equation while carbohydrate accumulation was modelled by an empirical function, analogous to a proportional controller activated by the limitation of available nitrogen. We also proposed to formulate the fermentation rate as a function of the total protein content when relevant data are available. The final model was used to successfully explain experiments taken from the literature, performed under normal and nitrogen-limited conditions. Our results revealed that Monod model is insufficient to explain biomass formation kinetics in nitrogen-limited fermentations of S. cerevisiae . The goodness-of-fit of the herewith proposed model is superior to that of previously published models, offering the means to predict, and thus control fermentations. Importance: Problematic fermentations still occur in the winemaking industrial practise. Problems include sluggish rates of fermentation, which have been linked to insufficient levels of assimilable nitrogen. Data and relevant models can help anticipate poor fermentation performance. In this work, we proposed a model to predict biomass growth and fermentation rate under nitrogen-limited conditions and tested its performance with previously published experimental data. Our results show that the well-known Monod equation does not suffice to explain biomass formation.


Author(s):  
Hellen Chebet ◽  
Johnson Kinyua ◽  
Patrick Kareru ◽  
Njiema Gitaari

The consumption of alcoholic drinks have highly risen recently to a situation whereby there is a deficit in the stores, this is due to the higher demand compared to supply. Due to the high prices of most of the industrialized brews, consumers have opted for locally brewed drinks. Although locally manufactured brews are not recognized and certified by law, most are of good quality and with low cost of production. The use of Tithonia diversifolia can be employed to aid in improvement of the rate of production of local and industrialized brews. The main aim of this project was to improve the rate of fermentation of alcoholic beverage using both Tithonia diversifolia leaves extracts and iron II nanoparticles derived from it. It was observed that the plant catalyst reduced the time taken to produce alcohol. Alcohol fermentation rate in presence of yeast and with a tithonia extract as catalyst was measured, Rates of alcohol production was measured by UV VIS at intervals of one hour and deduced from a calibration curve. From the data, the alcohol content was higher in the sample catalyzed by the complexed extract and the one containing extracts as the catalyst as compared to the one without a catalyst. The percentage ethanol was able to be detected by finding absorbances (beer lambert law A = e l c.).


2021 ◽  
Vol 655 (1) ◽  
pp. 012012
Author(s):  
M. E. Ojewumi ◽  
J.A. Omoleye ◽  
A.A. Ajayi ◽  
G.P. Ekanem
Keyword(s):  

2021 ◽  
Author(s):  
David Henriques ◽  
Eva Balsa-Canto

ABSTRACTThe yeast Saccharomyces cerevisiae is an essential microorganism in food biotechnology; particularly, in wine and beer making. During wine fermentation, yeasts transform sugars present in the grape juice into ethanol and carbon dioxide. The process occurs in batch conditions and is, for the most part, an anaerobic process. Previous studies linked limited-nitrogen conditions with problematic fermentations, with negative consequences for the performance of the process and the quality of the final product. It is, therefore, of the highest interest to anticipate such problems through mathematical models. Here we propose a model to explain problematic fermentations under nitrogen-limited anaerobic conditions. We separated the biomass formation into two phases: growth and carbohydrate accumulation. Growth was modelled using the well-known Monod law while carbohydrate accumulation was modelled by an empirical function, analogous to a proportional controller activated by the limitation of available nitrogen. We also proposed to formulate the fermentation rate as a function of the total protein content when relevant data are available. The final model was used to successfully explain a series of experiments taken from the literature, performed under normal and nitrogen-limited conditions. Our results revealed that Monod law is insufficient to explain biomass formation kinetics in nitrogen-limited fermentations of S. cerevisiae. The goodness-of-fit of the herewith proposed model is superior to that of previously published models, offering the means to predict, and thus control, problematic fermentations.IMPORTANCEProblematic fermentations still occur in the winemaking industrial practise. Problems include sluggish rates of fermentation, which have been linked to insufficient levels of assimilable nitrogen. Data and relevant models can help anticipate poor fermentation performance. In this work, we proposed a model to predict biomass growth and fermentation rate under nitrogen-limited conditions and tested its performance with previously published experimental data. Our results show that the well-known Monod law does not suffice to explain biomass formation. A second term accounting for carbohydrate accumulation is required to predict successfully, and thus control, problematic fermentations.


Foods ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1133
Author(s):  
Ana C. Ribeiro ◽  
Álvaro T. Lemos ◽  
Rita P. Lopes ◽  
Maria J. Mota ◽  
Rita S. Inácio ◽  
...  

Food fermentation under pressure has been studied in recent years as a way to produce foods with novel properties. The purpose of this work was to study kefir production under pressure (7–50 MPa) at different temperatures (17–32 °C), as a case study of unconventional food fermentation. The fermentation time to produce kefir was similar at all temperatures (17, 25, and 32 °C) up to 15 MPa, compared to atmospheric pressure. At 50 MPa, the fermentation rate was slower, but the difference was reduced as temperature increased. During fermentation, lactic and acetic acid concentration increased while citric acid decreased. The positive activation volumes (Va) obtained indicate that pressure decreased the fermentation rate, while the temperature rise led to the attenuation of the pressure effect (lower Va). On the other hand, higher activation energies (Ea) were observed with pressure increase, indicating that fermentation became more sensitive to temperature. The condition that resulted in a faster fermentation, higher titratable acidity, and higher concentration of lactic acid was 15 MPa/32 °C. As the authors are aware, this is the second work in the literature to study the combined effect of pressure and temperature on a fermentative process.


HortScience ◽  
2020 ◽  
Vol 55 (8) ◽  
pp. 1356-1364 ◽  
Author(s):  
Adam D. Karl ◽  
Michael G. Brown ◽  
Sihui Ma ◽  
Ann Sandbrook ◽  
Amanda C. Stewart ◽  
...  

Yeast assimilable nitrogen (YAN) can be a limiting nutritional factor for Saccharomyces cerevisiae yeast when fermenting apple (Malus ×domestica Borkh.) juice into hard cider. Endogenous YAN concentrations in apples are often below the recommended thresholds to completely use all of the fermentable sugar and minimize the production of off-flavors, such as hydrogen sulfide. Cider producers supplement apple juice with exogenous nitrogen to increase YAN. Urea, commonly applied to apple orchards to increase fruit size and yields, was tested for its ability to increase endogenous apple juice YAN. Starting 6 weeks before harvest in 2017 and 2018, a 1% urea solution was applied to ‘Red Spy’ apple trees one, three, or five times to create low-, medium-, and high-rate treatments, respectively. Relative to the control, the high treatment increased YAN by 229% in 2017 and by 408% in 2018. More than 90% of the YAN in all juice samples was composed of primary amino nitrogen (PAN). Among all treatments, PAN mostly comprised asparagine, and as urea applications increased, the relative concentration of asparagine also increased. Aspartic acid and then glutamic acid were the second and third most abundant amino acids in all treatments, respectively, but comprised less of the total PAN as the number of urea applications increased. Soluble solid concentration, pH, titratable acidity, and total polyphenol concentration were not different among treatments. There was a positive correlation between increased urea application rate and the maximum fermentation rate, which resulted in a shorter fermentation duration. Increasing the number of urea applications was also correlated with greater hydrogen sulfide (H2S) production in juice fermented from fruit harvested in 2017 but not for fruit harvested in 2018. No residual H2S was found in the finished cider from any treatment. Increasing the number of urea applications was estimated to be less expensive than supplementing the juice with Fermaid O™. There would have been no cost savings if Fermaid K™ was used as an exogenous nitrogen source. Foliar urea applications were estimated to be more expensive than supplementing juice with diammonium phosphate. This study demonstrated that foliar urea applications can effectively increase YAN concentration in cider apples while not negatively affecting other juice quality attributes.


2020 ◽  
Vol 68 (4) ◽  
pp. 1091-1100 ◽  
Author(s):  
Nannan Guan ◽  
Xiaowei He ◽  
Shaokang Wang ◽  
Feitong Liu ◽  
Qiang Huang ◽  
...  

2020 ◽  
Vol 69 (9) ◽  
pp. 1031-1041
Author(s):  
Dong-Hui Geng ◽  
Lu Liu ◽  
Sumei Zhou ◽  
Xiaobin Sun ◽  
Lili Wang ◽  
...  

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