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Related Experiment Video

Updated: Jul 3, 2026

Design and Use of a Low Cost, Automated Morbidostat for Adaptive Evolution of Bacteria Under Antibiotic Drug Selection

Design and Use of a Low Cost, Automated Morbidostat for Adaptive Evolution of Bacteria Under Antibiotic Drug Selection

Published on: September 27, 2016

Multirate state and parameter estimation in an antibiotic fermentation with delayed measurements.

R D Gudi¹, S L Shah, M R Gray

¹Department of Chemical Engineering, University of Alberta, Edmonton T6G 2G6, Canada.

Biotechnology and Bioengineering

|December 1, 1994

Summary

This study introduces a new method to monitor fermentation processes by combining endogenous decay and maintenance into a modified coefficient. This approach improves the estimation of biomass and growth rates, even with delayed measurements.

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Area of Science:

Biotechnology
Biochemical Engineering
Process Monitoring

Background:

Traditional software sensors like the extended Kalman filter (EKF) struggle with fermentation processes exhibiting endogenous metabolism and time-varying maintenance.
These culture-related activities complicate accurate estimation and monitoring of critical fermentation parameters.

Purpose of the Study:

To develop a robust multirate software sensor-based estimation strategy for monitoring fermentation processes.
To address the limitations of traditional algorithms in handling complex metabolic activities.
To accurately estimate biomass and specific growth rates in fed-batch fermentations.

Main Methods:

Lumped endogenous decay and maintenance into a modified maintenance coefficient, m(c).
Developed model equations relating measurable outputs (CER, biomass) to observable parameters (net specific growth rate, modified maintenance coefficient).
Implemented a multirate estimation strategy accommodating delayed biomass measurements and frequent CER measurements.

Main Results:

Successfully monitored biomass profiles and critical fermentation parameters, including specific growth rate.
Demonstrated the effectiveness of the modified maintenance coefficient approach.
Validated the multirate software sensor strategy in a fed-batch fermentation of Streptomyces clavuligerus.

Conclusions:

The proposed multirate software sensor strategy effectively monitors fermentation processes with endogenous metabolism and time-varying maintenance.
The modified maintenance coefficient approach enhances the accuracy of biomass and growth rate estimations.
This method offers a reliable solution for complex fermentation monitoring challenges.