Mathematical modeling of a batch bioreactor as a means of forming professional competence of masters of Biotechnology
DOI:
https://doi.org/10.38014/ehs-ss.2025.4.06Keywords:
students, HEI, competence-based approach, mathematical modeling, bioreactor, batch process, differential equations, Mathcad, Python, competencies, biotechnologyAbstract
Biotechnology is gaining increasing significance each year as a driver of innovative development in modern technological society, extending across a wide range of human activities including pharmacy, medicine, food and chemical industries and environmental sustainability. Consequently, the requirements for qualified
personnel in the biotechnology sector are rising, which enhances the demand for high-quality training of biotechnology students. Special emphasis is placed on mastering mathematical and computer modeling methods, which enable students to design, analyze, and optimize biotechnological processes in line with industrial needs and societal demands.
This study presents a mathematical description of the processes occurring in a batch bioreactor, the parameter optimization of which largely determines the efficiency of biotechnological production. The proposed model is based on the Michaelis–Menten and Monod equations, and the differential equations system is solved using the Odesolve operator in Mathcad 15, and the results reproduce characteristic kinetics of batch fermentation. The mathematical model describes the kinetic module of a batch bioreactor, accounting for microbial growth rate, substrate consumption, and product formation.
The developed model can be applied in real production processes and simultaneously possesses significant didactic value. It allows students to understand the role of mathematical and computer modeling in the design of various types of biotechnological processes, explore options for optimizing bioreactor parameters, and control growth kinetics and biochemical transformation rates. The students here acquire practical skills of dealing with the software, learn to apply modern digital technologies, analyze complex biotechnological systems, predict process behavior, interpret graphical results, make informed decisions, and evaluate production efficiency. Such an educational model contributes to the formation of professional competencies defined in the curriculae for specialty G21 Biotechnology and Bioengineering.
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Copyright (c) 2025 Natalia STUCHYNSKA, Maria ANDRIYCHUK
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