Determination of substantial chemical compounds of Agarwood oil for quality grading / Mohamad Hushnie Haron … [et al.]

Haron, Mohamad Hushnie and Taib, Mohd Nasir and Ismail, Nurlaila and Mohd Nor, Nor Azah and Tajuddin, Saiful Nizam (2020) Determination of substantial chemical compounds of Agarwood oil for quality grading / Mohamad Hushnie Haron … [et al.]. Journal of Electrical and Electronic Systems Research (JEESR), 17. pp. 50-59. ISSN 1985-5389

Abstract

Agarwood is a resin saturated heartwood producing its ownessential oil. This oil comprises of a complex mixture of chromone derivatives, oxygenated sesquiterpenes and sesquiterpene hydrocarbons. This mixture has a heavy woody scentand is one of the contributors to the Agarwood oil quality. In this paper, a study that focuses on the approach to select the substantial chemical compounds for Agarwood quality grading was carried out. GC-MS analysis was used to extract the chemical compounds from the Agarwood oil. The data were then preprocessed using techniques such as missing values ratio, natural logarithm and min. max. normalization. Next, synthetic data were generated using MUNGE to fulfil the passing condition of sampling adequacy test. To determine the substantial compounds, PCA and Pearson’s correlation were used. This approach was successful in determining three substantial compounds namely β-agarofuran, αagarofuran and 10-epi-γ-eudesmol. These substantial chemical compounds will be used later to predict the quality of Agarwood oil.

Metadata

Item Type: Article
Creators:
Creators
Email / ID Num.
Haron, Mohamad Hushnie
hushnieharon@gmail.com
Taib, Mohd Nasir
UNSPECIFIED
Ismail, Nurlaila
UNSPECIFIED
Mohd Nor, Nor Azah
UNSPECIFIED
Tajuddin, Saiful Nizam
UNSPECIFIED
Subjects: T Technology > TP Chemical technology > Adsorption
T Technology > TP Chemical technology > Oils, fats, and waxes
Divisions: Universiti Teknologi MARA, Shah Alam > Faculty of Electrical Engineering
Journal or Publication Title: Journal of Electrical and Electronic Systems Research (JEESR)
UiTM Journal Collections: UiTM Journal > Journal of Electrical and Electronic Systems Research (JEESR)
ISSN: 1985-5389
Volume: 17
Page Range: pp. 50-59
Keywords: Correlation, Principle Components Analysis, Statistical Analysis, Statistical Learning
Date: 2020
URI: https://ir.uitm.edu.my/id/eprint/42384
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