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

Production of Alcohol

Production of Alcohol

Continuous fermentation is a key strategy in industrial ethanol production, particularly when efficiency, scalability, and high yields are essential. This approach allows for uninterrupted operation and optimized resource utilization. The primary feedstock, corn starch, undergoes enzymatic hydrolysis facilitated by α-amylase and glucoamylase. These enzymes break down the starch into fermentable sugars such as glucose, which are readily assimilated by fermentative microorganisms.Fermentation...

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...

Bioreactor Controls-II

Bioreactor Controls-II

In aerobic fermentations, oxygen is vital for microbial growth and metabolite production. Since air comprises only about 20% oxygen and the gas is poorly soluble in water—just 9 ppm at 20°C—supplying sufficient oxygen becomes a critical challenge, especially in high-demand processes like yeast growth or citric acid production. Even a fully saturated broth may offer only a few seconds of oxygen availability.To address this, sterile or scrubbed air is introduced into the fermentor via a sparger...

Bioreactor Controls-I

Bioreactor Controls-I

Maintaining optimal conditions within fermenters is essential for maximizing microbial productivity and ensuring process efficiency. This lesson focuses on key parameters—temperature, foam, pH, carbon dioxide, oxygen, and pressure—and their precise measurement and control strategies in fermentation systems.Temperature ControlTemperature regulation is critical due to the exothermic nature of many fermentation processes. In small laboratory fermenters, temperature is commonly monitored using...

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...

You might also read

Related Articles

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

Sort by

Same author

External validation of established clinical risk scores for cancer-associated venous thromboembolism in a Brazilian registry.

Journal of thrombosis and thrombolysis·2026

Same author

Artificial intelligence in computational modeling of thrombosis: Bridging mechanistic insights and clinical translation.

Journal of thrombosis and thrombolysis·2025

Same author

Determination of Patient-Specific Blood Coagulation Kinetic Parameters via Neural Networks: Toward Thrombosis Prediction in Personalized Medicine.

Annals of biomedical engineering·2025

Same author

Integrating biomarkers for hemostatic disorders into computational models of blood clot formation: A systematic review.

Mathematical biosciences and engineering : MBE·2025

Same author

A Comparison of Monoglyceride Production from Microalgaelipids and Rapeseed Oil Catalyzed by Metal Oxides.

ChemSusChem·2024

Same author

Personalized lattice-structured prosthesis as a graftless solution for mandible reconstruction and prosthetic restoration: A finite element analysis.

Journal of the mechanical behavior of biomedical materials·2024

Search research articles

Related Experiment Video

Updated: Jun 20, 2026

Techniques for the Evolution of Robust Pentose-fermenting Yeast for Bioconversion of Lignocellulose to Ethanol

Techniques for the Evolution of Robust Pentose-fermenting Yeast for Bioconversion of Lignocellulose to Ethanol

Published on: October 24, 2016

Dynamics and control strategies for a butanol fermentation process.

Adriano Pinto Mariano¹, Caliane Bastos Borba Costa, Maria Regina Wolf Maciel

¹Laboratory of Optimization, Design and Advanced Control, LOPCA School of Chemical Engineering, University of Campinas, P.O. Box 6066, 13083-970 Campinas, São Paulo, Brazil. adrianomariano@yahoo.com.br

Applied Biochemistry and Biotechnology

|September 5, 2009

Summary

Mathematical modeling optimized butanol production via flash fermentation. A proportional-integral controller demonstrated superior performance, achieving faster, oscillation-free responses for enhanced process control.

More Related Videos

Light-Controlled Fermentations for Microbial Chemical and Protein Production

Light-Controlled Fermentations for Microbial Chemical and Protein Production

Published on: March 22, 2022

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

Related Experiment Videos

Last Updated: Jun 20, 2026

Techniques for the Evolution of Robust Pentose-fermenting Yeast for Bioconversion of Lignocellulose to Ethanol

Techniques for the Evolution of Robust Pentose-fermenting Yeast for Bioconversion of Lignocellulose to Ethanol

Published on: October 24, 2016

Light-Controlled Fermentations for Microbial Chemical and Protein Production

Light-Controlled Fermentations for Microbial Chemical and Protein Production

Published on: March 22, 2022

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

Area of Science:

Biochemical Engineering
Process Control
Mathematical Modeling

Background:

Flash fermentation offers continuous butanol recovery from fermentation broth.
Process stability is challenged by dynamic disturbances in substrate concentration and operating conditions.

Purpose of the Study:

To model and analyze the dynamic behavior of a flash fermentation process for butanol production.
To develop and evaluate feedback control strategies (SISO and MIMO) for process regulation and set-point tracking.
To compare the performance of Dynamic Matrix Control (DMC) and Proportional-Integral (PI) controllers.

Main Methods:

Development of a mathematical model for the interconnected fermentor, cell retention, and vacuum flash vessel units.
Implementation and simulation of single-input/single-output (SISO) and multiple-input/multiple-output (MIMO) control strategies.
Comparative performance analysis of DMC and PI controllers under process disturbances.

Main Results:

Both DMC and PI controllers effectively managed process perturbations, maintaining stable operating conditions.
The PI controller exhibited superior performance, characterized by faster response times and absence of oscillations.
The study successfully demonstrated the feasibility of controlling key parameters like sugar and butanol concentrations.

Conclusions:

Mathematical modeling provides a robust framework for understanding and controlling complex bioprocesses like flash fermentation.
Proportional-Integral (PI) control is a highly effective and efficient strategy for optimizing butanol production dynamics.
Advanced control strategies can be implemented to ensure consistent product recovery and process stability.