Software sensors for fermentation processes

Area of Science:

• Biotechnology
• Microbial Physiology
• Process Engineering

Background:

• Fed-batch fermentation is crucial for microbial production.
• Monitoring key state variables in real-time is essential for process control.
• Existing methods may not fully capture cellular energy demands.

Purpose of the Study:

• To develop and validate software sensors for real-time monitoring of Escherichia coli fed-batch cultures.
• To introduce a novel R(O/S) sensor to assess energy substrate consumption and physiological stress.
• To correlate sensor outputs with biomass concentration, specific growth rate, and oxygen transfer capacity.

Main Methods:

• Utilized standard on-line fermentation data.
• Developed simple mathematical models for software sensor implementation.
• Monitored biomass concentration, specific growth rate, and oxygen transfer capacity.
• Introduced and analyzed the R(O/S) sensor (ratio of oxygen to energy substrate consumption).

Main Results:

• Software sensors successfully monitored key state variables in Escherichia coli fed-batch processes.
• The R(O/S) sensor demonstrated continuous increase with constant glucose feed, reflecting rising maintenance energy demand.
• R(O/S) sensor showed sensitivity to pH shift-downs, indicating increased energy demand for survival.
• The R(O/S) sensor shows potential for monitoring physiological stress.

Conclusions:

• Software sensors provide effective real-time monitoring of Escherichia coli fed-batch fermentation.
• The R(O/S) sensor is a promising tool for assessing cellular energy status and physiological stress.
• This approach can enhance process understanding and control in microbial cultivations.