Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Scale-Up Processes

Scale-Up Processes

The scale-up of microbial fermentation processes is essential in industrial biotechnology, allowing the transition from laboratory-scale experiments to commercial-scale production while aiming to maintain product yield and quality. This process requires meticulous adjustment of equipment design, process parameters, and contamination control strategies to accommodate increasing culture volumes.At the laboratory scale, cultures are typically maintained in 1 to 10-liter glass or autoclavable...

Bioreactor Controls-III

Bioreactor Controls-III

Strain improvement is a foundational strategy in industrial microbiology aimed at maximizing microbial productivity, particularly because natural isolates typically yield commercially valuable products in very low concentrations. Although optimizing the culture medium and environmental conditions can improve yields, these adjustments are inherently limited by the organism’s genetic potential. As a result, the focus shifts toward genetic modifications to enhance biosynthetic capacity. The...

Batch vs Continuous Culture

Batch vs Continuous Culture

Fermentation is a foundational biotechnological process used to produce pharmaceuticals, biofuels, enzymes, and food additives. Among industrial strategies, batch and continuous fermentation are the two most widely applied. Although both rely on microbial conversion of substrates into desired products, they differ markedly in operation, productivity, and suitability for specific applications.Batch fermentation occurs in a closed system in which nutrient media and inoculum are added at the...

Bioreactor Design and Operational System

Bioreactor Design and Operational System

Bioreactors are engineered vessels designed to cultivate microorganisms under controlled conditions for industrial bioprocessing. They maintain sterility and allow precise regulation of pH, temperature, oxygen, and nutrient levels to optimize microbial growth and metabolite production. Bioreactors range from small laboratory units of 1 liter to industrial systems holding up to 500,000 liters, though only about 75% of their volume is actively used for fermentation. The remaining headspace...

Upstream Processing

Upstream Processing

Upstream processing represents a critical phase in biomanufacturing, wherein biological systems such as microorganisms, mammalian cells, or insect cells are cultivated to produce therapeutic proteins, vaccines, enzymes, or other biologically derived products. This phase encompasses all steps from the selection and genetic manipulation of the production organism to the cultivation of cells in bioreactors under tightly controlled environmental conditions.Host Selection and Genetic OptimizationThe...

Fed-Batch Culture

Fed-Batch Culture

Fed-batch culture is a widely used bioprocessing strategy combining aspects of batch culture with controlled substrate feeding to optimize cell growth and product formation. In this semi-closed system, nutrients are strategically added during fermentation, while the accumulated products and biomass remain within the bioreactor until the end of the operation. This controlled addition of substrates allows for better management of growth kinetics, nutrient limitation, and metabolite...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

The Potential of Fermentation-Based Processing on Protein Modification: A Review.

Foods (Basel, Switzerland)·2025

Same author

Transfer learning for quantitative image analysis of biosolids.

Water science and technology : a journal of the International Association on Water Pollution Research·2025

Same author

Extension of first principle elemental balancing soft-sensors by nonlinear reaction kinetics for increased robustness in bioprocess monitoring.

Bioprocess and biosystems engineering·2024

Same author

Raman spectroscopy and one-dimensional convolutional neural network modeling as a real-time monitoring tool for in vitro transaminase-catalyzed synthesis of a pharmaceutically relevant amine precursor.

Biotechnology progress·2024

Same author

Addressing raw material variability: In-line FTIR sugar composition analysis of lignocellulosic process streams.

Bioresource technology·2024

Same author

Bringing a scalable adaptive hybrid modeling framework closer to industrial use: Application on a multiscale fungal fermentation.

Biotechnology and bioengineering·2024

Search research articles

Related Experiment Video

Updated: Jun 4, 2026

Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology

Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology

Published on: December 15, 2017

Hybrid modeling for industrial fermentation processes with an "Intra-Batch Experimental Design".

Marc Lemperle¹, Pedram Ramin¹, Julian Kager¹

¹Process and Systems Engineering Center (PROSYS), Department of Chemical and Biochemical Engineering, Technical University of Denmark Søltofts Plads, DK-2800 Kgs. Lyngby, Denmark.

Journal of Industrial Microbiology & Biotechnology

|June 2, 2026

Summary

This summary is machine-generated.

This study introduces a new framework for modeling fungal fermentation viscosity, reducing experimental costs and offline measurements. The hybrid model improves process optimization and supports automated model development for industrial applications.

Keywords:

experimental design hybrid modeling industrial fermentation oxygen transfer rate

More Related Videos

Process Optimization using High Throughput Automated Micro-Bioreactors in Chinese Hamster Ovary Cell Cultivation

Process Optimization using High Throughput Automated Micro-Bioreactors in Chinese Hamster Ovary Cell Cultivation

Published on: May 18, 2020

Workflow Based on the Combination of Isotopic Tracer Experiments to Investigate Microbial Metabolism of Multiple Nutrient Sources

Workflow Based on the Combination of Isotopic Tracer Experiments to Investigate Microbial Metabolism of Multiple Nutrient Sources

Published on: January 22, 2018

Related Experiment Videos

Last Updated: Jun 4, 2026

Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology

Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology

Published on: December 15, 2017

Process Optimization using High Throughput Automated Micro-Bioreactors in Chinese Hamster Ovary Cell Cultivation

Process Optimization using High Throughput Automated Micro-Bioreactors in Chinese Hamster Ovary Cell Cultivation

Published on: May 18, 2020

Workflow Based on the Combination of Isotopic Tracer Experiments to Investigate Microbial Metabolism of Multiple Nutrient Sources

Workflow Based on the Combination of Isotopic Tracer Experiments to Investigate Microbial Metabolism of Multiple Nutrient Sources

Published on: January 22, 2018

Area of Science:

Biotechnology
Chemical Engineering
Process Systems Engineering

Background:

Accurate modeling of oxygen transfer rate is crucial for fungal fermentation optimization.
Traditional viscosity models are complex, requiring extensive offline measurements.
Digital twins/shadows for fermentation require high-fidelity process models.

Purpose of the Study:

To develop a novel, cost-effective framework for modeling fungal fermentation viscosity.
To reduce reliance on tedious offline rheological measurements.
To integrate online sensor data for improved predictive modeling.

Main Methods:

Developed a model for oxygen mass transfer coefficient (kLa) using reduced fermentation runs.
Evaluated three machine learning algorithms as soft sensors for online viscosity prediction.
Created a hybrid model combining mechanistic and data-driven approaches.

Main Results:

Achieved R² of 0.92 with online data vs. 0.67 with offline data for kLa modeling.
Reduced experimental effort for kLa model development from nine to two fermentations.
Hybrid model accurately predicted fermentation dynamics across various conditions with modest accuracy improvements.

Conclusions:

Online sensor integration significantly enhances mathematical model development.
The proposed framework lowers costs and effort for model development.
This work advances automated model development for industrial fermentation processes.