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Fermentation
Special Issues
Modeling and Simulation of Fermentation
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Modeling and Simulation of Fermentation

A special issue of Fermentation (ISSN 2311-5637). This special issue belongs to the section "Fermentation Process Design".

Deadline for manuscript submissions: closed (15 April 2022) | Viewed by 12501

Special Issue Editor

Prof. Dr. Kurt A. Rosentrater

E-Mail Website
Guest Editor
Department of Agricultural and Biosystems Engineering, Iowa State University, Ames, IA 50011, USA
Interests: industrial fermentation; industrial microbiology; biofuels; beverage alcohols; distilled spirits; beer; life cycle assessment; efficiencies; technoeconomic analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Throughout human history, carbohydrates have been fermented into alcohols for human consumption, especially for beer, wine, whiskey, and other alcoholic beverages.  In recent years, we have also witnessed tremendous growth in the research, development, and commercialization of many biorenewable resources. Starches, lipids, proteins, and fibers can now be utilized to produce a variety of bio-based energy, fuels, products, chemicals, and other renewable materials. Many countries have experienced exponential growth in biofuel production, such as maize- and sugarcane-based ethanol, as well as soy, canola, palm, and other oilseed-based biodiesel. Biochemicals such as succinic acid, muconic acid, triacetic acid lactone, bioplastics such as polylactic acid, glycerol-based bioadhesives, and other bio-based products are increasingly being commercialized as well. Although the science, engineering, and technology of conversion and utilization are progressing, there is a critical need for more detailed studies on fermentation and separation processes, the conditions used, and impacts on final products. This Special Issue is particularly interested in studies that focus on the modeling and simulation of industrial fermentation and bioprocessing systems. Computer simulation has the potential to amalgamate knowledge mathematically and allow predictions of processing behaviors and final product yields and qualities, based on system inputs and operational conditions, and thus can play an important role in developing control algorithms, systems, and strategies—whether the fermentation is used for human beverages or other bio-based products.

Prof. Dr. Kurt A. Rosentrater
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Fermentation is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • batch fermentation
  • beer
  • biochemicals
  • bioenergy
  • biofuels
  • bioproducts
  • biorenewables
  • contamination
  • continuous fermentation
  • enzyme kinetics
  • fermentation
  • inhibitors
  • modeling
  • monod kinetics
  • simulation
  • whiskey/whisky
  • wine

Published Papers (4 papers)

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Research

16 pages, 3043 KiB  
Article
Kinetics of Lignin Removal from Rice Husk Using Hydrogen Peroxide and Combined Hydrogen Peroxide–Aqueous Ammonia Pretreatments
by Novia Novia, Hasanudin Hasanudin, Hermansyah Hermansyah and Ahmad Fudholi
Fermentation 2022, 8(4), 157; https://doi.org/10.3390/fermentation8040157 - 01 Apr 2022
Cited by 7 | Viewed by 2948
Abstract
The rice husk has the potential to be used for converting agricultural wastes into renewable energy. Therefore, this study aims to improve the hydrolysis of rice husk through Hydrogen Peroxide (HP) and Combined Hydrogen Peroxide–Aqueous Ammonia (CHPA) pretreatments. The removal of lignin from [...] Read more.
The rice husk has the potential to be used for converting agricultural wastes into renewable energy. Therefore, this study aims to improve the hydrolysis of rice husk through Hydrogen Peroxide (HP) and Combined Hydrogen Peroxide–Aqueous Ammonia (CHPA) pretreatments. The removal of lignin from rice husks was determined using SEM–EDS examination of the samples. At a specific concentration of H2O2, (CHPA) pretreatment eliminated a significantly larger amount of lignin from biomass. The percentage of lignin removal of HP varied from 48.25 to 66.50, while CHPA ranged from 72.22 to 85.73. Hence, the use of batch kinetics of lignin removal of both pretreatments is recommended, where the kinetic parameters are determined by fitting the experimental data. Based on the results, the activation energies for HP and CHPA pretreatments were 9.96 and 7.44 kJ/mol, which showed that the24 model is appropriate for the experimental data. The increase in temperatures also led to a higher pretreatment value, indicating their positive correlation. Meanwhile, CHPA pretreatment was subjected to enzymatic hydrolysis of 6% enzyme loading for the production of 6.58 g glucose/L at 25 h. Full article
(This article belongs to the Special Issue Modeling and Simulation of Fermentation)
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20 pages, 10224 KiB  
Article
Modeling Anaerobic Co-Digestion of Corn Stover Hydrochar and Food Waste for Sustainable Biogas Production
by Ibrahim Shaba Mohammed, Risu Na and Naoto Shimizu
Fermentation 2022, 8(3), 110; https://doi.org/10.3390/fermentation8030110 - 03 Mar 2022
Cited by 3 | Viewed by 2730
Abstract
Despite the importance of the biodegradability of lignocellulose biomass, few studies have evaluated the lignocellulose biomass digestion kinetics and modeling of the process. Anaerobic digestion (AD) is a mature energy production technique in which lignocellulose biomass is converted into biogas. However, using different [...] Read more.
Despite the importance of the biodegradability of lignocellulose biomass, few studies have evaluated the lignocellulose biomass digestion kinetics and modeling of the process. Anaerobic digestion (AD) is a mature energy production technique in which lignocellulose biomass is converted into biogas. However, using different organic waste fractions in AD plants is challenging. In this study, lignocellulose biomass (corn stover hydrochar) obtained from hydrothermal carbonization at a temperature, residential time, and biomass/water ratio of 215 °C, 45 min, and 0.115, respectively, was added to the bioreactor as a substrate inoculated with food waste and cow dung to generate biogas. A state–space AD model containing one algebraic equation and two differential equations was constructed. All the parameters used in the model were dependent on the AD process conditions. An adaptive identifier system was developed to automatically estimate parameter values from input and output data. This made it possible to operate the system under different conditions. Daily cumulative biogas production was predicted using the model, and goodness-of-fit analysis indicated that the predicted biogas production values had accuracies of >90% during both model construction and validation. Future work will focus on the application of modeling predictive control into an AD system that would comprise both models and parameters estimation. Full article
(This article belongs to the Special Issue Modeling and Simulation of Fermentation)
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29 pages, 9914 KiB  
Article
Investigating a Stirred Bioreactor: Impact of Evolving Fermentation Broth Pseudoplastic Rheology on Mixing Mechanisms
by M. Constanza Sadino-Riquelme, José Rivas, David Jeison, Andrés Donoso-Bravo and Robert E. Hayes
Fermentation 2022, 8(3), 102; https://doi.org/10.3390/fermentation8030102 - 28 Feb 2022
Cited by 5 | Viewed by 3164
Abstract
The culture medium in many fermentations is a non-Newtonian fluid. In bacterial alginate batch production, the broth becomes more pseudoplastic as the alginate concentration increases, which impairs the mixing process. This work characterizes the effect of the interaction between changing broth rheology and [...] Read more.
The culture medium in many fermentations is a non-Newtonian fluid. In bacterial alginate batch production, the broth becomes more pseudoplastic as the alginate concentration increases, which impairs the mixing process. This work characterizes the effect of the interaction between changing broth rheology and impeller mixing on a bioreactor fluid dynamics. Experimentally, a fermentation with evolving broth pseudoplastic rheology is reproduced. Three fermentation stages are mimicked using appropriate solutions of water and xanthan gum. Impeller torque measurements are reported. The weakening of the impellers’ interaction over the fermentation process is identified. To overcome the experimental limitations, CFD is applied to study the evolution of the fermentation fluid flow patterns, velocity field, dead zones, and vortical structures. Precessional vortex macro-instabilities are identified as being responsible for the unstable flow patterns identified at the earlier stages of the fermentation. A stable parallel flow pattern accounts for the weakest impellers’ interaction at the final stage. Overall, this work contributes with a complete workflow to adapt CFD models for characterization and aided design of stirred tanks with changing broth pseudoplastic rheology as well as an evolving flow regime. Full article
(This article belongs to the Special Issue Modeling and Simulation of Fermentation)
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17 pages, 1932 KiB  
Article
Modeling and Use of Inter-Criteria Decision Analysis for Selecting Growth Rate Models for Batch Cultivation of Yeast Kluyveromyces marxianus var. lactis MC 5
by Mitko Petrov
Fermentation 2021, 7(3), 163; https://doi.org/10.3390/fermentation7030163 - 22 Aug 2021
Cited by 3 | Viewed by 1972
Abstract
Ten unstructured models of Monod, Mink, Tessier, Moser, Aiba, Andrews, Haldane, Luong, Edward, and Han-Levenspiel are considered in this paper to explain the kinetics of cell growth for batch cultivation of the yeast Kluyweromyces marxianus var. lactis MC 5. For the first time, [...] Read more.
Ten unstructured models of Monod, Mink, Tessier, Moser, Aiba, Andrews, Haldane, Luong, Edward, and Han-Levenspiel are considered in this paper to explain the kinetics of cell growth for batch cultivation of the yeast Kluyweromyces marxianus var. lactis MC 5. For the first time, two independent kinetic models are used to model the process for the two basic substrates—lactose and oxygen. The selection of the most appropriate growth rate models has been made through a new multi-criteria decision-making approach called the Inter-Criteria Decision Analysis (ICDA) method. The application of ICDA to the growth rate of lactose and oxygen alone has shown that there have been many correlations between the studied models. Thus, the models for the growth rate, depending only on lactose, are reduced to one—Monod model and there are two models—Monod and Mink—depending on oxygen only. Separate kinetic process models have been developed for the combination of Monod–Monod and Monod–Mink models. For the first time, in addition to the multiplicative form, the additive form of a specific growth rate has been studied. The comparison of the obtained results has shown that the additive form has shown better results than the multiplicative one. For this reason, the additive form of the Monod–Monod model will be used to model the process. Full article
(This article belongs to the Special Issue Modeling and Simulation of Fermentation)
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