Application of self-organizing map for modeling the Aquilaria malaccensis oil using chemical compound
Abstract
Agarwood oil, known as ‘black gold’ or the ‘wood of God,’ is a globally prized essential oil derived naturally from the Aquilaria tree. Despite its significance, the current non-standardized grading system varies worldwide, relying on subjective assessments. This paper addresses the need for a consistent classification model by presenting an overview of Aquilaria malaccensis oil quality using the self-organizing map (SOM) algorithm. Derived from the Thymelaeaceae family, Aquilaria malaccensis is a primary source of agarwood trees in the Malay Archipelago. Agarwood oil extraction involves traditional methods like solvent extraction and hydro-distillation, yielding a complex mixture of chromone derivatives, oxygenated sesquiterpenes, and sesquiterpene hydrocarbons. This study categorizes agarwood oil into high and low grades based on chemical compounds, utilizing the SOM algorithm with inputs of three specific compounds: β-agarofuran, α-agarofuran, and 10-epi-φ-eudesmol. Findings demonstrate the efficacy of SOM-based quality grading in distinguishing agarwood oil grades, offering a significant contribution to the field. The non-standardized grading system's inefficiency and subjectivity underscore the necessity for a standardized model, making this research crucial for the agarwood industry's advancement.
Keywords
Agarwood oil; Aquilaria species; Grading classification; Self-organizing map; System identification
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PDFDOI: http://doi.org/10.11591/ijai.v14.i4.pp2889-2898
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IAES International Journal of Artificial Intelligence (IJ-AI)
ISSN/e-ISSN 2089-4872/2252-8938
This journal is published by the Institute of Advanced Engineering and Science (IAES).