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Processes
Special Issues
Knowledge-Based Control and Modelling of Bioprocesses
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Knowledge-Based Control and Modelling of Bioprocesses

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Biological Processes and Systems".

Deadline for manuscript submissions: closed (15 November 2021) | Viewed by 2957

Special Issue Editor

Prof. Dr. Karel Melzoch

E-Mail Website
Guest Editor
Department of Biotechnology, University of Chemistry and Technology, Prague, Technicka 5, 16628 Prague 6, Czech Republic
Interests: production of primary and secondary metabolites by microbial cells; production of recombinant proteins; production of alternative biofuels from biomass; biorefinery (biomass treatment); bioengineering; bioprocess modeling and control; downstream processing

Special Issue Information

Dear Colleagues,

The current biotechnology industry contributes significantly to increasing the global economy. Its growth is mainly attributed to a deep understanding of biological systems, supported by the development of "omics" technologies and the growing demand for biotechnological products such as biopharmaceuticals, vaccines or biofuels. Today, it is an innovative market, and there is growing business pressure for faster and cheaper bioproduct production. Improvements in data digitization and analysis have been identified as key strategic actions for the coming years to meet these challenges. The implementation of knowledge‐based control and modeling in various bioprocess presents a corresponding future vision for the biotechnology industry to achieve the goals of Industry 4.0.

Prof. Dr. Karel Melzoch
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. Processes 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 2400 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

  • biotechnology
  • fermentation chemistry and technology
  • bioengineering
  • downstream processing
  • biorefinery
  • exploitation of wastes from agriculture and food processing

Published Papers (1 paper)

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Research

19 pages, 2118 KiB  
Article
Development of a Digital Twin for Enzymatic Hydrolysis Processes
by Christian Appl, Frank Baganz and Volker C. Hass
Processes 2021, 9(10), 1734; https://0-doi-org.brum.beds.ac.uk/10.3390/pr9101734 - 28 Sep 2021
Cited by 2 | Viewed by 2372
Abstract
Enzymatic hydrolysis processes can be used to produce organic nutrient media from renewable raw materials. However, many of these processes are not optimally designed, so expensive enzymes and substrates are wasted. Mathematical models and Digital Twins (DTs) are powerful tools, which can be [...] Read more.
Enzymatic hydrolysis processes can be used to produce organic nutrient media from renewable raw materials. However, many of these processes are not optimally designed, so expensive enzymes and substrates are wasted. Mathematical models and Digital Twins (DTs) are powerful tools, which can be used to optimize bioprocesses and, thus, increase the yield of the desired products. Individual enzymatic hydrolysis processes have already been modeled, but models for the combined starch hydrolysis and proteolysis, or DTs, are not available yet. Therefore, an easily adaptable, dynamic, and mechanistic mathematical model representing the kinetics of the enzymatic hydrolysis process of the combined starch hydrolysis and proteolysis was developed and parameterized using experimental data. The model can simulate the starch hydrolysis process with an agreement of over 90% and the proteolysis process with an agreement of over 85%. Subsequently, this model was implemented into an existing DT of a 20 L stirred tank reactor (STR). Since the DT cannot only map the kinetics of the enzymatic process, but also the STR with the associated periphery (pumps, heating jacket, etc.), it is ideally suited for future process control strategy development and thus for the optimization of enzymatic hydrolysis processes. Full article
(This article belongs to the Special Issue Knowledge-Based Control and Modelling of Bioprocesses)
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