Differentiating Agarwood Oil Quality Using Artificial Neural Network

Agarwood oil is well known as expensive oil extracted from the resinous of fragrant heartwood. The oil is getting high demand in the market especially from the Middle East countries, China and Japan because of its unique odor. As part of an on-going research in grading the agarwood oil quality, the...

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Main Authors:	Saiful Nizam, Tajuddin, Nurlaila, Ismail, Nor Azah, Mohd Ali, Mailina, Jamil, Mohd Hezri, Fazalul Rahiman, Mohd Nasir, Taib
Format:	Article
Language:	English
Published:	Universiti Kebangsaan Malaysia 2013
Subjects:	Q Science (General) QD Chemistry
Online Access:	http://umpir.ump.edu.my/id/eprint/6253/ http://umpir.ump.edu.my/id/eprint/6253/ http://umpir.ump.edu.my/id/eprint/6253/1/Differentiating_Agarwood_Oil_Quality_Using_Artificial_Neural_Network.pdf

id	ump-6253
recordtype	eprints
spelling	ump-62532018-05-01T23:38:16Z http://umpir.ump.edu.my/id/eprint/6253/ Differentiating Agarwood Oil Quality Using Artificial Neural Network Saiful Nizam, Tajuddin Nurlaila, Ismail Nor Azah, Mohd Ali Mailina, Jamil Mohd Hezri, Fazalul Rahiman Mohd Nasir, Taib Q Science (General) QD Chemistry Agarwood oil is well known as expensive oil extracted from the resinous of fragrant heartwood. The oil is getting high demand in the market especially from the Middle East countries, China and Japan because of its unique odor. As part of an on-going research in grading the agarwood oil quality, the application of Artificial Neural Network (ANN) is proposed in this study to analyze agarwood oil quality using its chemical profiles. The work involves of selected agarwood oil from low and high quality,the extraction of chemical compounds using GC-MS and Z-score to identify of the significant compounds as input to the network. The ANN programming algorithm was developed and computed automatically via Matlab software version R2010a. Back-propagation training algorithm and sigmoid transfer function were used to optimize the parameters in the training network. The result obtained showed the capability of ANN in analyzing the agarwood oil quality hence beneficial for the further application such as grading and classification for agarwood oil. Universiti Kebangsaan Malaysia 2013 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/6253/1/Differentiating_Agarwood_Oil_Quality_Using_Artificial_Neural_Network.pdf Saiful Nizam, Tajuddin and Nurlaila, Ismail and Nor Azah, Mohd Ali and Mailina, Jamil and Mohd Hezri, Fazalul Rahiman and Mohd Nasir, Taib (2013) Differentiating Agarwood Oil Quality Using Artificial Neural Network. Malaysian Journal of Analytical Sciences, 17 (3). pp. 490-498. ISSN 1394-2506 http://www.ukm.my/mjas/v17_n3/Nor%20Azah.pdf
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	Q Science (General) QD Chemistry
spellingShingle	Q Science (General) QD Chemistry Saiful Nizam, Tajuddin Nurlaila, Ismail Nor Azah, Mohd Ali Mailina, Jamil Mohd Hezri, Fazalul Rahiman Mohd Nasir, Taib Differentiating Agarwood Oil Quality Using Artificial Neural Network
description	Agarwood oil is well known as expensive oil extracted from the resinous of fragrant heartwood. The oil is getting high demand in the market especially from the Middle East countries, China and Japan because of its unique odor. As part of an on-going research in grading the agarwood oil quality, the application of Artificial Neural Network (ANN) is proposed in this study to analyze agarwood oil quality using its chemical profiles. The work involves of selected agarwood oil from low and high quality,the extraction of chemical compounds using GC-MS and Z-score to identify of the significant compounds as input to the network. The ANN programming algorithm was developed and computed automatically via Matlab software version R2010a. Back-propagation training algorithm and sigmoid transfer function were used to optimize the parameters in the training network. The result obtained showed the capability of ANN in analyzing the agarwood oil quality hence beneficial for the further application such as grading and classification for agarwood oil.
format	Article
author	Saiful Nizam, Tajuddin Nurlaila, Ismail Nor Azah, Mohd Ali Mailina, Jamil Mohd Hezri, Fazalul Rahiman Mohd Nasir, Taib
author_facet	Saiful Nizam, Tajuddin Nurlaila, Ismail Nor Azah, Mohd Ali Mailina, Jamil Mohd Hezri, Fazalul Rahiman Mohd Nasir, Taib
author_sort	Saiful Nizam, Tajuddin
title	Differentiating Agarwood Oil Quality Using Artificial Neural Network
title_short	Differentiating Agarwood Oil Quality Using Artificial Neural Network
title_full	Differentiating Agarwood Oil Quality Using Artificial Neural Network
title_fullStr	Differentiating Agarwood Oil Quality Using Artificial Neural Network
title_full_unstemmed	Differentiating Agarwood Oil Quality Using Artificial Neural Network
title_sort	differentiating agarwood oil quality using artificial neural network
publisher	Universiti Kebangsaan Malaysia
publishDate	2013
url	http://umpir.ump.edu.my/id/eprint/6253/ http://umpir.ump.edu.my/id/eprint/6253/ http://umpir.ump.edu.my/id/eprint/6253/1/Differentiating_Agarwood_Oil_Quality_Using_Artificial_Neural_Network.pdf
first_indexed	2023-09-18T22:01:51Z
last_indexed	2023-09-18T22:01:51Z
_version_	1777414450914000896

Differentiating Agarwood Oil Quality Using Artificial Neural Network

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