OBJECTIVE To establish a quantitative analysis of multi‑components by single‑marker (QAMS) method for the simultaneous determination of five phenylpropanoid components (coumarin, cinnamyl alcohol, cinnamic acid, cinnamaldehyde, and o⁃methoxycinnamaldehyde) in Cinnamomi Ramulus, and to comprehensively evaluate the quality of samples from different origins (Zhaoqing, Guangdong; Wuzhou, Guangxi; Yulin, Guangxi) using multivariate statistical analysis.

METHODS Separation was performed on a Waters ACQUITY UPLC BEH C₁₈ column (100 mm × 2.1 mm, 1.7 μm) using a mobile phase consisting of 0.1% formic acid in water (A) and acetonitrile (B) with gradient elution. The flow rate was 0.4 mL·min⁻¹, the UV detection wavelength was set at 254 nm, the column temperature was maintained at 25 ℃, and the injection volume was 1 μL. Using cinnamic acid as the internal reference substance, relative correction factors for coumarin, cinnamyl alcohol, cinnamaldehyde, and o‑methoxycinnamaldehyde were established to achieve simultaneous quantification. Partial least squares‑discriminant analysis (PLS‑DA) was employed for data processing, and variable importance in projection (VIP) values were used to identify differential components.

RESULTS The content of phenylpropanoid components (except cinnamyl alcohol) determined by the QAMS method showed no significant difference compared with those obtained by the external standard method. The relative correction factors for coumarin, cinnamaldehyde, and o‑methoxycinnamaldehyde relative to cinnamic acid were 5.920, 4.434, and 8.087, respectively, with good reproducibility (RSD<5.0%) under different experimental conditions. Cinnamic acid was identified as the major differential component among samples from different origins.

CONCLUSION The established QAMS method combined with multivariate statistical analysis can be effectively used for quality evaluation of Cinnamomi Ramulus from different growing regions.