The potential of artificial neural network (ANN) in optimizing media constituents of citric acid production by solid state bioconversion

The potential of artificial neural network (ANN) in optimizing media constituents of citric acid production by solid state bioconversion

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 networks (ANN) approach. The bioconversion process was done through solid state bioconversion using Aspergillus niger. ANN model was bu...

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Main Authors: Nasaruddin, Ricca Rahman, Jami, Mohammed Saedi, Alam, Md. Zahangir
Format: Article
Language:English
Published: Faculty of Food Science and Technology, Universiti Putra Malaysia 2012
Subjects:
TP155 Chemical engineering
Online Access:http://irep.iium.edu.my/22414/
http://irep.iium.edu.my/22414/
http://irep.iium.edu.my/22414/1/%2816%29_Saedi_%281%29.pdf
id iium-22414
recordtype eprints
spelling iium-224142017-08-10T01:46:58Z http://irep.iium.edu.my/22414/ The potential of artificial neural network (ANN) in optimizing media constituents of citric acid production by solid state bioconversion Nasaruddin, Ricca Rahman Jami, Mohammed Saedi Alam, Md. Zahangir TP155 Chemical engineering 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 networks (ANN) approach. The bioconversion process was done through solid state bioconversion using Aspergillus niger. ANN model was built using MATLAB software. A dataset consists of 20 runs from our previous work was used to develop ANN. The predictive and generalization ability of ANN and the results of RSM were compared. The determination coefficients (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. Faculty of Food Science and Technology, Universiti Putra Malaysia 2012-02-01 Article PeerReviewed application/pdf en http://irep.iium.edu.my/22414/1/%2816%29_Saedi_%281%29.pdf Nasaruddin, Ricca Rahman and Jami, Mohammed Saedi and Alam, Md. Zahangir (2012) The potential of artificial neural network (ANN) in optimizing media constituents of citric acid production by solid state bioconversion. International Food Research Journal, 19 (2). pp. 491-497. ISSN 1985-4668 (P), 2231-7546 (O) http://www.ifrj.upm.edu.my/19%20(02)%202012/(16)IFRJ-2012%20Saedi.pdf
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
topic TP155 Chemical engineering
spellingShingle TP155 Chemical engineering
Nasaruddin, Ricca Rahman
Jami, Mohammed Saedi
Alam, Md. Zahangir
The potential of artificial neural network (ANN) in optimizing media constituents of citric acid production by solid state bioconversion
description 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 networks (ANN) approach. The bioconversion process was done through solid state bioconversion using Aspergillus niger. ANN model was built using MATLAB software. A dataset consists of 20 runs from our previous work was used to develop ANN. The predictive and generalization ability of ANN and the results of RSM were compared. The determination coefficients (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.
format Article
author Nasaruddin, Ricca Rahman
Jami, Mohammed Saedi
Alam, Md. Zahangir
author_facet Nasaruddin, Ricca Rahman
Jami, Mohammed Saedi
Alam, Md. Zahangir
author_sort Nasaruddin, Ricca Rahman
title The potential of artificial neural network (ANN) in optimizing media constituents of citric acid production by solid state bioconversion
title_short The potential of artificial neural network (ANN) in optimizing media constituents of citric acid production by solid state bioconversion
title_full The potential of artificial neural network (ANN) in optimizing media constituents of citric acid production by solid state bioconversion
title_fullStr The potential of artificial neural network (ANN) in optimizing media constituents of citric acid production by solid state bioconversion
title_full_unstemmed The potential of artificial neural network (ANN) in optimizing media constituents of citric acid production by solid state bioconversion
title_sort potential of artificial neural network (ann) in optimizing media constituents of citric acid production by solid state bioconversion
publisher Faculty of Food Science and Technology, Universiti Putra Malaysia
publishDate 2012
url http://irep.iium.edu.my/22414/
http://irep.iium.edu.my/22414/
http://irep.iium.edu.my/22414/1/%2816%29_Saedi_%281%29.pdf
first_indexed 2023-09-18T20:34:11Z
last_indexed 2023-09-18T20:34:11Z
_version_ 1777408935987249152

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