Gender discrimination of barks by HPLC fingerprint combined with multivariate statistics.

A high-performance liquid chromatography (HPLC) fingerprint method with multivariate statistical analyses was applied to discriminate the male and female barks of for the first time. The samples of 11 male and 13 female barks of mature were collected in Beijing. The chemical fingerprint of methanol extract was established by HPLC method with diode array detector (DAD). The principal component analysis (PCA), hierarchical clustering analysis (HCA), and supervised orthogonal partial least squares discriminant analysis (OPLS-DA) were applied to discriminate male and female barks based on the area of common peaks identified in HPLC fingerprints. A clear grouping trend ( , 0.83; , 0.595) among the male and female samples was exhibited by PCA score plot. Two groups were clearly divided into male and female samples by HCA. Both male and female samples were well discriminated with OPLS-DA ( , 0.775; , 0.795). Seven potential chemical markers were screened by variable importance in projection (VIP values >1.0) of OPLS-DA model and four of them were identified as micranthoside, siebolside B, sakuranin, and isosakuranin. The HPLC fingerprint combined with multivariate statistical analyses could be used to discriminate the gender of barks of and revealed the differences in chemical components, which enriched the basic studies on dioecious plant.