The potential of artificial neural network (ANN) in optimizing bioconversion process: in case of media constituents of citric acid production from palm oil Empty Fruit Bunches (EFB)
This work aims at optimizing the media constituents for citric acid production from oil palm empty fruit bunches (EFB) as renewable resource using artificial neural network (ANN) approach. The bioconversion process was done through solid state bioconversion using Aspergillus niger. ANN model was bui...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/3170/ http://irep.iium.edu.my/3170/ http://irep.iium.edu.my/3170/1/Final_ICBIOE_2011_-_ANN_-_Ricca.pdf |
| Summary: | This work aims at optimizing the media constituents for citric acid production from oil palm empty fruit bunches (EFB) as renewable resource using artificial neural network (ANN) approach. The bioconversion process was done through solid state bioconversion using Aspergillus niger. ANN model was built using MATLAB software. A 20 dataset of an earlier published paper was used to developed ANN. The predictive and generalization ability of ANN and the results of RSM in the used published paper were compared. The determination coefficient (R2-value) for ANN and RSM models were 0.997 and 0.985, respectively, indicating the superiority of ANN in capturing the non-linear behavior of the system. Validation process was done and the maximum citric acid production (147.74 g/kg-EFB) was achieved using the optimal solution from ANN which consists of 6.1% sucrose, 9.2% mineral solution and 15.0% inoculum. |
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