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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/6253/1/Differentiating_Agarwood_Oil_Quality_Using_Artificial_Neural_Network.pdf
http://umpir.ump.edu.my/id/eprint/6253/
http://www.ukm.my/mjas/v17_n3/Nor%20Azah.pdf
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spelling my.ump.umpir.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
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
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/6253/1/Differentiating_Agarwood_Oil_Quality_Using_Artificial_Neural_Network.pdf
http://umpir.ump.edu.my/id/eprint/6253/
http://www.ukm.my/mjas/v17_n3/Nor%20Azah.pdf
_version_ 1643665336243847168
score 13.211869

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