Harnessing Raman Spectroscopy for Enhanced Bioprocess Monitoring: Predictive CO<sub>2</sub> Analysis and Robust pH Determination in Bioreactor Off-Gas Stream
The accurate measurement of CO<sub>2</sub> concentration in fermentation off-gas is crucial for monitoring and optimizing bioprocesses, particularly in mammalian cell cultures. In this study, we successfully utilized Raman off-gas spectroscopy to achieve time-resolved prediction of CO<...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | Fermentation |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2311-5637/11/6/317 |
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| Summary: | The accurate measurement of CO<sub>2</sub> concentration in fermentation off-gas is crucial for monitoring and optimizing bioprocesses, particularly in mammalian cell cultures. In this study, we successfully utilized Raman off-gas spectroscopy to achieve time-resolved prediction of CO<sub>2</sub> concentrations in the fermentation off-gas. Our experiments were conducted using two different media: a commercial medium (medium 1) and an in-house Roche medium (medium 2), each tested with two different lots. The results demonstrated that Raman spectroscopy provides precise and real-time CO<sub>2</sub> measurements, which are essential for effective process monitoring and control. Furthermore, we established that CO<sub>2</sub> off-gas analysis can be directly correlated with the pH value of the fermentation medium. This correlation allows for accurate pH prediction with comparable precision to traditional methods, where CO<sub>2</sub> levels are first determined via Raman spectroscopy or an off-gas analyzer and then used to infer pH through a correlation curve. In the final step of our study, we employed a Raman submers probe to predict CO<sub>2</sub> and pH directly within the fermentation medium. Compared to the model accuracy in the off-gas stream, the performance of the Raman submers probe in predicting CO<sub>2</sub> and pH within the medium was significantly worse, likely due to the absence of a pretrained model for CO<sub>2</sub>. Our findings highlight the potential of Raman off-gas spectroscopy as a powerful tool for real-time bioprocess monitoring and control, offering significant advantages in terms of accuracy and efficiency. |
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| ISSN: | 2311-5637 |