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Methanol Independent Expression by Pichia Pastoris Employing De-repression Technologies
Published on: January 23, 2019
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Research on Soft-Sensing Method Based on Adam-FCNN Inversion in Pichia pastoris Fermentation.
Bo Wang1, Wenyu Ma1, Hui Jiang1
1School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China.
Sensors (Basel, Switzerland)
|July 12, 2025
Summary
This study introduces a novel soft-sensing method using an Adam-Fully Connected Neural Network inverse for Pichia pastoris fermentation. The approach enhances real-time prediction accuracy for critical biological parameters in complex bioprocesses.
Area of Science:
- Biotechnology
- Process Engineering
- Computational Biology
Background:
- Pichia pastoris fermentation presents challenges in modeling and optimization due to nonlinear dynamic coupling.
- Real-time measurement of key biological parameters is difficult, hindering process control.
Purpose of the Study:
- To develop an effective soft-sensing method for accurate prediction of biological parameters in Pichia pastoris fermentation.
- To address nonlinearities and measurement difficulties in bioprocesses.
Main Methods:
- Constructed a non-deterministic mechanism model to characterize dynamic coupling.
- Utilized a Fully Connected Neural Network (FCNN) with an Adam optimizer to identify an inverse extended model.
- Implemented an adaptive learning rate optimization algorithm for FCNN convergence.
- Formed a composite pseudo-linear system by cascading the inverse model with the original system.
Main Results:
- Achieved decoupling of the complex fermentation system.
- Demonstrated high-accuracy prediction of key biological parameters.
- Significantly reduced prediction errors compared to traditional models.
- Enhanced generalization capabilities of the prediction model.
Conclusions:
- The proposed Adam-FCNN inverse soft-sensing method is effective for complex bioprocesses.
- The method successfully addresses nonlinear dynamic coupling and measurement challenges.
- Validated effectiveness in Pichia pastoris fermentation for improved process understanding and control.
