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Identification of chemical markers for species differentiation in Aquilaria essential oils using self-organizing maps

Noramli, Nur Athirah SyafiqahRoslan, Muhammad IkhsanAhmad Sabri, Noor Aida SyakiraIsmail, NurlailaMohd Yusoff, ZakiahTaib, Mohd Nasir
IAES International Journal of Artificial Intelligence (IJ-AI) (Sinta 1)Vol. 0 No. 01 April 2026
DOI10.11591/ijai.v15.i2.pp1339-1348

Abstrak

This study analyzes the chemical diversity of essential oils from four Aquilaria species, A. beccariana, A. malaccensis, A. crassna, and A. subintegra, which are important sources of agarwood used in perfumery and traditional medicine. Despite their economic and ecological value, the chemical profiles of these species remain insufficiently characterized, hindering accurate species differentiation and resource management. This research aims to identify distinctive chemical patterns to improve species classification. Self-organizing maps (SOMs) were employed to analyze complex chemical composition data and to identify significant compounds responsible for species separation. The analysis revealed several compounds with strong discriminatory power and species-specific distribution patterns, with compounds C, D, and E identified as the most significant markers. These findings demonstrate substantial biochemical diversity among Aquilaria species and confirm the effectiveness of SOM for essential oil profiling. The results support improved species identification and have important implications for ecological conservation, sustainable agarwood management, and pharmacological development.

Kata Kunci

AgarwoodAquilaria speciesChemical diversityEssential oilsSelf-organizing mapsSignificant chemical compoundsSpecies classification

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Identification of chemical markers for species differentiation in Aquilaria essential oils using self-organizing maps | IAES International Journal of Artificial Intelligence (IJ-AI) | Publiora