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

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Main Authors:	Nasaruddin, Ricca Rahman, Jami, Mohammed Saedi, Alam, Md. Zahangir
Format:	Article
Language:	English
Published:	Faculty of Food Science & Technology, Universiti Putra Malaysia (UPM) 2012
Subjects:	TP Chemical technology TP155 Chemical engineering TP248.13 Biotechnology
Online Access:	http://irep.iium.edu.my/66292/ http://irep.iium.edu.my/66292/ http://irep.iium.edu.my/66292/1/66292_The%20potential%20of%20artificial%20neural%20network%20%28ANN%29.pdf

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recordtype	eprints
spelling	iium-662922019-07-12T02:30:32Z http://irep.iium.edu.my/66292/ 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 TP Chemical technology TP155 Chemical engineering TP248.13 Biotechnology This work aims at optimizing the media constituents for citric acid production from oil palm empty fruit bunches (EFB) as renewable resource using artifiial 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 coeffiients (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 & Technology, Universiti Putra Malaysia (UPM) 2012 Article PeerReviewed application/pdf en http://irep.iium.edu.my/66292/1/66292_The%20potential%20of%20artificial%20neural%20network%20%28ANN%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 2231 7546 http://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	TP Chemical technology TP155 Chemical engineering TP248.13 Biotechnology
spellingShingle	TP Chemical technology TP155 Chemical engineering TP248.13 Biotechnology 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 artifiial 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 coeffiients (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 & Technology, Universiti Putra Malaysia (UPM)
publishDate	2012
url	http://irep.iium.edu.my/66292/ http://irep.iium.edu.my/66292/ http://irep.iium.edu.my/66292/1/66292_The%20potential%20of%20artificial%20neural%20network%20%28ANN%29.pdf
first_indexed	2023-09-18T21:34:06Z
last_indexed	2023-09-18T21:34:06Z
_version_	1777412705450196992

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

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