Raman Spectroscopy-Based Glucose Feed Control Automates Malic Acid Fermentation

Area of Science:

• Biotechnology and metabolic engineering
• Process analytical technology (PAT)
• Chemical engineering

Background:

• Fermentation optimization is crucial for the economic viability of biotechnology.
• Traditional substrate feeding lacks precise control, leading to limitations or inefficiencies.
• Online monitoring is essential for real-time adjustments in bioprocesses.

Purpose of the Study:

• To implement Raman spectroscopy for closed-loop glucose feed control during malic acid production.
• To develop an automated feedback system for precise substrate management.
• To optimize the production of malic acid, a valuable platform chemical.

Main Methods:

• Utilized Raman spectroscopy for real-time online monitoring of glucose and malic acid concentrations.
• Developed a Partial Least Squares (PLS) regression model for accurate concentration prediction.
• Implemented a Proportional-Integral-Derivative (PID) controller for automated feedback-controlled glucose feeding.

Main Results:

• Achieved real-time monitoring with a root mean square error of prediction of 2.7 g/L for glucose and 5.3 g/L for malic acid.
• Maintained a constant glucose concentration of 20 g/L during the production phase via automated feedback.
• Successfully stopped substrate feeding automatically upon monitoring product inhibition to prevent substrate loss.

Conclusions:

• Raman spectroscopy provides a practical and effective method for real-time fermentation monitoring and control.
• Automated feedback systems based on online monitoring significantly improve bioprocess efficiency and yield.
• This approach demonstrates the practical relevance and feasibility of advanced PAT in industrial biotechnology.