PRINCIPAL COMPONENT ANALYSIS AND CLUSTER ANALYSIS TO EVALUATE THE SEASONAL VARIATION IN THE CHEMICAL COMPOSITION OF TEA TREE OIL

Abstract

The tea tree, scientifically known as Melaleuca alterfolia (Maiden & Betche) Cheel, is native to Australia and has strong antibacterial, antifungal, and antiviral properties. The purpose of this study was to evaluate the influence of seasonal variation on the yield and chemical composition of tea tree oil over a 12-month period. Tea tree oil was extracted by the hydrodistillation method in the support of a surfactant solution (650 ppm). During the survey period, the essential oil content ranged from 4.24% to 6.61%. The constituents of TTO were determined using GC-FID and GC-MS, as well as multivariate analysis: principal component analysis (PCA) and cluster analysis. Nine main components in TTO were a-pinene (2.0-2.5%), 1,8-cineole (3.2-5.5%), a-terpinene (8.3-12.1%), p-cymene (1.8-4.3%), limonene (1.0-1.4%), g-terpinene (16.1-21.4%), terpinolene (2.1–3.5%), terpinen-4-ol (40.6–49.6%), and a- terpineol (3.1–6.6%). The results of the analysis showed that the essential oil content was highest during the summer months when there was a lot of rain, while the composition of the main compounds in the essential oil changed almost insignificantly depending on the season. Furthermore, the antibacterial activity of pure tea tree oil and a few main components was evaluated