| Abstrakt: |
With the aggravation of environmental pollution and energy crisis, the sustainable microbial fermentation process of converting glycerol to 1,3‐propanediol (1,3‐PDO) has become an attractive alternative. However, the difficulty in the online measurement of glycerol and 1,3‐PDO creates a barrier to the fermentation process and then leads to the residual glycerol and therefore, its wastage. Thus, in the present study, the four‐input artificial neural network (ANN) model was developed successfully to predict the concentration of glycerol, 1,3‐PDO, and biomass with high accuracy. Moreover, an ANN model combined with a kinetic model was also successfully developed to simulate the fed‐batch fermentation process accurately. Hence, a soft sensor from the ANN model based on NaOH‐related parameters has been successfully developed which cannot only be applied in software to solve the difficulty of glycerol and 1,3‐PDO online measurement during the industrialization process, but also offer insight and reference for similar fermentation processes. [ABSTRACT FROM AUTHOR] |
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