Visualization OPLS class models of GC-MS-based metabolomics data for identifying agarwood essential oil extracted by hydro-distillation

Abstract

Abstract The composition of natural substances varies with plant species and cultivation environment factors, which is also a complex problem. A total of 127 substances of agarwood essential oils (AEOs) extracted by hydro-distillation were identified by GC-MS analysis. Among the components obtained from AEOs, sesquiterpenes and small molecule aromatic substances were the main components, and there were significantly fewer chromones. The aromatic compound 4-phenyl-2-butanone was the only common component. The VIP value and S-plot generated by the OPLS-DA model based on the comparison of regional groups or pairwise genotypes showed up to 26 potential markers at VIP > 1. The more common components of agarwood, such as sesquiterpenes α-guruene, agarospirol, guaiol, γ-eudesmol and chromone 2-phenylethyl-4H-chromen-4-one, contributed the most to the VIP value. Supervised OPLS-DA was better than that of PLS-DA, providing a reference for the quality evaluation of AEOs. This method emphasizes providing more information and obtaining additional information when combined with appropriate multivariate modeling and effective visualization of specific labeled metabolites for identification.

Keywords

• Agarwood
• Essential oil
• GC-MS
• Chemometrics
• OPLS-DA