Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
3.7
3.7
Journals
Fermentation
Special Issues
Modeling Methods for Fermentation Processes
share announcement

Modeling Methods for Fermentation Processes

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

Deadline for manuscript submissions: closed (28 February 2024) | Viewed by 10181

Special Issue Editor

Prof. Dr. Peter Götz

E-Mail Website
Guest Editor
Department of Bioprocess Engineering, Berliner Hochschule für Technik, Berlin, Germany
Interests: fermentation; mathematical modelling; numerical analysis; bioprocess engineering and fermentation

Special Issue Information

Dear Colleagues,

Since the advent of modern biotechnology initiated scientific research towards quantitative analysis of fermentation processes, various modeling tools have been applied and newly devised. This started around 50 years ago with the transfer of knowledge from chemical engineering to describe bioreactors, using mainly empirical equations, accompanied by unstructured models for the biological reactions. Capturing the complexity of living systems in more detail then led to the research field of systems biology, utilizing mechanistic models down to a molecular level. Beyond empirical and mechanistic models, a third approach to fermentation modeling is evolving, which is data-driven (e.g., machine learning).

Advanced applications of modeling are culminating in the current development of digital twins for industrial production processes. For fermentation processes, it ultimately means modeling an in silico cell within an industrial scale bioprocess environment, adding even more complexity to this task due to the multiscale nature of this combination. Another feature of a digital twin is the integration of real-time data into model simulations for process analysis and control, leading to hybrid modeling concepts via combinations of modeling methods.

This Special Issue aims to collect state-of-the-art publications on all modeling methods and their hybrid variants, from basic research to applications in industry, to provide an overview and initiate the creation of new approaches. Strengthening modeling will improve the efficiency, sustainability, and profitability of fermentation-based industries by understanding the underlying mechanisms of the system, optimizing the process parameters, and minimizing waste generation and resource consumption.

Prof. Dr. Peter Götz
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

  • fermentation
  • bioprocess
  • bioreactor
  • modeling
  • empirical modeling
  • mechanistic modeling
  • machine learning
  • data science
  • metabolic modeling
  • systems biology
  • in silico cell
  • digital twin

Published Papers (7 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

23 pages, 4827 KiB  
Article
Model Identification of E. coli Cultivation Process Applying Hybrid Crow Search Algorithm
by Olympia Roeva and Dafina Zoteva
Fermentation 2024, 10(1), 12; https://doi.org/10.3390/fermentation10010012 - 22 Dec 2023
Viewed by 1049
Abstract
Cultivation process (CP) modeling and optimization are ambitious tasks due to the nonlinear nature of the models and interdependent parameters. The identification procedures for such models are challenging. Metaheuristic algorithms exhibit promising performance for such complex problems since a near-optimal solution can be [...] Read more.
Cultivation process (CP) modeling and optimization are ambitious tasks due to the nonlinear nature of the models and interdependent parameters. The identification procedures for such models are challenging. Metaheuristic algorithms exhibit promising performance for such complex problems since a near-optimal solution can be found in an acceptable time. The present research explores a new hybrid metaheuristic algorithm built upon the good exploration of the genetic algorithm (GA) and the exploitation of the crow search algorithm (CSA). The efficiency of the proposed GA-CSA hybrid is studied with the model parameter identification procedure of the E. coli BL21(DE3)pPhyt109 fed-batch cultivation process. The results are compared with those of the pure GA and pure CSA applied to the same problem. A comparison with two deterministic algorithms, i.e., sequential quadratic programming (SQP) and the Quasi-Newton (Q-N) method, is also provided. A more accurate model is obtained by the GA-CSA hybrid with fewer computational resources. Although SQP and Q-N find a solution for a smaller number of function evaluations, the resulting models are not as accurate as the models generated by the three metaheuristic algorithms. The InterCriteria analysis, a mathematical approach to revealing certain relations between given criteria, and a series of statistical tests are employed to prove that there is a statistically significant difference between the results of the three stochastic algorithms. The obtained mathematical models are then successfully verified with a different set of experimental data, in which, again, the closest one is the GA-CSA model. The GA-CSA hybrid proposed in this paper is proven to be successful in the collaborative hybridization of GA and CSA with outstanding performance. Full article
(This article belongs to the Special Issue Modeling Methods for Fermentation Processes)
►▼ Show Figures

Figure 1

19 pages, 1770 KiB  
Article
Physical Factors Affecting the Scale-Up of Vegetative Insecticidal Protein (Vip3A) Production by Bacillus thuringiensis Bt294
by Kwanruthai Malairuang, Pumin Nutaratat, Borworn Werapan, Somjit Komwijit, Chutchanun Trakulnaleamsai, Netnapa Phosrithong, Amporn Rungrod, Boonhiang Promdonkoy and Wai Prathumpai
Fermentation 2023, 9(11), 980; https://doi.org/10.3390/fermentation9110980 - 16 Nov 2023
Viewed by 1190
Abstract
Vip3A (vegetative insecticidal protein) is a representative member of the Vip3 family, which is widely used for lepidopteran pest control. This Vip3A protein, a non-growth-associated protein, is an effective bioinsecticide against insect pests, but there is relatively little information about its production processes [...] Read more.
Vip3A (vegetative insecticidal protein) is a representative member of the Vip3 family, which is widely used for lepidopteran pest control. This Vip3A protein, a non-growth-associated protein, is an effective bioinsecticide against insect pests, but there is relatively little information about its production processes at large scales. Hence, the effects of environmental factors on Vip3A production by Bacillus thuringiensis Bt294 (antifoam agents, shaking speeds, agitation and aeration rates), as well as controlling physical conditions such as the lowest point of dissolved oxygen and controlling of culture pH, were observed in shaking flasks and bioreactors. The results showed that antifoam agents, flask types and shaking speeds had significant effects on Vip3A and biomass production. Cultivation without pH control and DO control in 5 L bioreactors at lower agitation and aeration rates, which was not favorable for biomass production, resulted in a high Vip3A protein production of 5645.67 mg/L. The scale-up studies of the Vip3A protein production in a pilot-scale 750 L bioreactor gave 3750.0 mg/L. Therefore, this study demonstrated the significant effects of agitation, aeration rates and culture pH on Vip3A production by B. thuringiensis Bt294. Balancing of physical conditions was necessary for obtaining the highest yield of Vip3A by slowing down the production rate of biomass. Moreover, this Vip3A protein has high potential as a bioinsecticide for lepidopteran pest control in organic crops. This information will be important for significantly increasing the Vip3A protein concentration by the bacterium and will be useful for field application at a lower cost. Full article
(This article belongs to the Special Issue Modeling Methods for Fermentation Processes)
►▼ Show Figures

Figure 1

17 pages, 6154 KiB  
Article
Innocell Bioreactor: An Open-Source Development to Produce Biomaterials for Food and Packaging Based on Fermentation Processes
by Nitzan Cohen, Emma Sicher, Camilo Ayala-Garcia, Ignacio Merino Sanchez-Fayos, Lorenza Conterno and Secil Ugur Yavuz
Fermentation 2023, 9(10), 915; https://doi.org/10.3390/fermentation9100915 - 18 Oct 2023
Viewed by 1992
Abstract
A growing number of science and design scholars and design practitioners have recently embarked on studying fermentation processes to produce alternative materials. The main driver of this trend is the search for a sustainable future by proposing novel alternatives that could substitute or [...] Read more.
A growing number of science and design scholars and design practitioners have recently embarked on studying fermentation processes to produce alternative materials. The main driver of this trend is the search for a sustainable future by proposing novel alternatives that could substitute or integrate into society’s current production and consumption models. This study presents the development of an open-source bioreactor capable of enhancing and optimizing a symbiotic culture of bacteria and yeast (SCOBY) production process. The bioreactor is part of a greater design-driven project aiming to process edible and non-edible materials. The study presents the experiments and methods that led to the development and refinement of the current bioreactor, and all the information needed to replicate it with tools and equipment currently available under the Creative Commons status. The aim of sharing open-source methods and results to reproduce the bioreactor is to support different interdisciplinary teams of scientists and designers in generating high amounts of SCOBY, accelerating R&D with this auspicious yet underexplored source of bacterial cellulose. Full article
(This article belongs to the Special Issue Modeling Methods for Fermentation Processes)
►▼ Show Figures

Figure 1

16 pages, 4290 KiB  
Article
Implementing an Agent-Based Modeling Approach for Protein Glycosylation in the Golgi Apparatus
by Christian Jetschni and Peter Götz
Fermentation 2023, 9(9), 849; https://doi.org/10.3390/fermentation9090849 - 15 Sep 2023
Viewed by 1057
Abstract
Glycoproteins are involved in various significant biological processes and have critical biological functions in physiology and pathology by regulating biological activities and molecular signaling pathways. The variety of enzymes used in protein glycosylation and the wide range of diversity in the resulting glycoproteins [...] Read more.
Glycoproteins are involved in various significant biological processes and have critical biological functions in physiology and pathology by regulating biological activities and molecular signaling pathways. The variety of enzymes used in protein glycosylation and the wide range of diversity in the resulting glycoproteins pose a challenging task when attempting to simulate these processes in silico. This study aimed to establish and define the necessary structures to simulate the process of N-glycosylation in silico. In this article, we represent the process of glycosylation in the Golgi structure in an agent-based model with defined movement patterns and reaction rules between the associated proteins and enzymes acting as agents. The Golgi structure is converted into a grid consisting of 150 × 400 patches representing four compartments which contain a specific distribution of the fundamental enzymes contributing to the process of glycosylation. The interacting glycoproteins and membrane-bound enzymes are perceived as agents, with their own rules for movement, complex formation, biochemical reaction and dissociation. The resulting structures were saved into an XML-format, a mass spectrometry file and a GlycoWorkbench2-compatible file for visualization. Full article
(This article belongs to the Special Issue Modeling Methods for Fermentation Processes)
►▼ Show Figures

Figure 1

12 pages, 1247 KiB  
Article
Evaluation of Long-Term Fermentation Performance with Engineered Saccharomyces cerevisiae Strains
by Maarten L. De Mol, Victoria Marcoen, Isabelle Maryns, Nico Snoeck, Joeri J. Beauprez, Sofie L. De Maeseneire and Wim K. Soetaert
Fermentation 2023, 9(8), 721; https://doi.org/10.3390/fermentation9080721 - 30 Jul 2023
Cited by 1 | Viewed by 1456
Abstract
The performance of a microbial fermentation on an industrial scale is subjected to the robustness of the strain. Such strains are genetically engineered to optimize the production of desired compounds in minimal time, but they often fail to maintain high productivity levels for [...] Read more.
The performance of a microbial fermentation on an industrial scale is subjected to the robustness of the strain. Such strains are genetically engineered to optimize the production of desired compounds in minimal time, but they often fail to maintain high productivity levels for many generations, hindering their effective application in industrial conditions. This study focused on assessing the impact of genomic instability in yeasts that were engineered to produce a fluorescent output by incorporating a reporter gene at one or more genomic locations. The fermentation performance of these strains was evaluated over 100 generations in a sequential batch set-up. In order to bridge the gap between strain engineering and industrial implementation, we proposed the use of novel, host-specific parameters to standardize the strain robustness and evaluate potential improvements. It was observed that yeasts carrying multiple copies of the reporter gene exhibited a more pronounced decrease in output, and the genomic integration site significantly influenced the production. By leveraging these new, host-specific parameters, it becomes possible to anticipate strain behavior prior to incurring substantial costs associated with large-scale production. This approach enhances the economic viability of novel microbial fermentation processes and narrows the divide between laboratory findings and industrial applications. Full article
(This article belongs to the Special Issue Modeling Methods for Fermentation Processes)
►▼ Show Figures

Figure 1

27 pages, 2459 KiB  
Article
Kinetic Analysis of Gluconacetobacter diazotrophicus Cultivated on a Bench Scale: Modeling the Effect of pH and Design of a Sucrose-Based Medium
by Gloria M. Restrepo, Alejandro Rincón and Óscar J. Sánchez
Fermentation 2023, 9(8), 705; https://doi.org/10.3390/fermentation9080705 - 26 Jul 2023
Cited by 1 | Viewed by 1055
Abstract
Gluconacetobacter diazotrophicus is an endophytic bacterium that has shown important plant growth-promoting properties. During the growth of G. diazotrophicus with high carbon source concentrations, organic acids are produced, and pH decreases, thus inhibiting biomass growth. The objective of this work was to design [...] Read more.
Gluconacetobacter diazotrophicus is an endophytic bacterium that has shown important plant growth-promoting properties. During the growth of G. diazotrophicus with high carbon source concentrations, organic acids are produced, and pH decreases, thus inhibiting biomass growth. The objective of this work was to design a sucrose-based medium and perform a kinetic analysis of the batch submerged cultivation of this bacterium in a 3 L stirred-tank bioreactor without pH control. A mathematical model was proposed for representing G. diazotrophicus concentration, considering the inhibitory effect of hydrogen ion concentration. It comprises a biomass growth model, a specific growth rate expression that accounts for the inhibitory effect of hydrogen concentration, and a hydrogen model that represents the relationship between hydrogen and biomass concentrations. The sucrose-based medium proved its suitability for G. diazotrophicus growth. A higher biomass concentration (1.10 g/L) was obtained in a modified LGI-P medium containing 30 g/L sucrose with a three-fold increase in biomass production relative to the initial inoculation. The model allowed a satisfactory description of the experimental data obtained, and it could be used to design a cultivation strategy to maximize biomass production leading to the production of an alternative microbial inoculant for plant growth promotion of economically important crops. Full article
(This article belongs to the Special Issue Modeling Methods for Fermentation Processes)
►▼ Show Figures

Figure 1

13 pages, 1835 KiB  
Article
Investigating the Anaerobic Digestion of Water Hyacinth (Eichhornia crassipes) Sourced from Hartbeespoort Dam in South Africa
by Trevor M. Simbayi, Charles Rashama, Ayo A. Awosusi, Rosina Nkuna, Riann Christian and Tonderayi S. Matambo
Fermentation 2023, 9(7), 685; https://doi.org/10.3390/fermentation9070685 - 20 Jul 2023
Viewed by 1521
Abstract
The biodegradability of water hyacinth for biogas and biofertilizer production was studied under mesophilic conditions. The effects of water hyacinth pretreatments were also included in this investigation. It was found that water hyacinth has a low biodegradability of 27% when monodigested, while in [...] Read more.
The biodegradability of water hyacinth for biogas and biofertilizer production was studied under mesophilic conditions. The effects of water hyacinth pretreatments were also included in this investigation. It was found that water hyacinth has a low biodegradability of 27% when monodigested, while in a 3:1 ratio with cow manure, the biodegradability increases to 46%. At this elevated biodegradability, the water hyacinth biomethane potential was 185 LCH4/kgVS, while that of cow manure was 216 LCH4/kgVS. The Gompertz kinetic model had superior parameters than the logistic model for most of the water hyacinth–cow manure combined substrate digestion. Based on the Gompertz model, the lag phase and daily maximum methane production rate were 5.5 days and 22.9 mL/day, respectively, for the 3:1 codigestion (R2 of 0.99). These values were 6.7 days and 15.2 mL/day, respectively, in the case of water hyacinth monodigestion (R2 = 0.996). The dominant microbial species detected in the digestates were Bacteroidetes and Proteobacteria. A few microbial species were indigenous to water hyacinth, but more diverse consortia, which are key to efficient substrate biodegradation, came from cow manure. The digestate contained ammonium nitrogen at 68 mg/kg with phosphorous and potassium at 73 and 424 mg/kg, respectively. Nitrogen was lower but phosphorous and potassium were comparable to previously studied digestates of other substrates. Only water hyacinth pretreated by aerobic composting was proven to unlock a higher methane yield that matched the 3:1 codigestion with cow manure. Other pretreatments induced better biodegradation performance than that observed in untreated water hyacinth but these improvements were not as good as that of the 3:1 codigestion scheme. It was concluded that water hyacinth sourced from the Hartbeespoort Dam could be treated by anaerobic digestion to recover biogas and biofertilizer. However, more experiments are required to fully understand and harness the optimisation opportunities available in applying this technology to manage water hyacinths. Full article
(This article belongs to the Special Issue Modeling Methods for Fermentation Processes)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-7
Back to TopTop