Objective  To establish the HPLC fingerprints of Platycladi Cacumen from different origins and evaluate its quality through chemical pattern recognition.

Methods  An HPLC method was adopted. The determination was performed on a ZORBAX Eclipse plus-C₁₈ (250 mm×4.6 mm, 5 μm) column with mobile phase consisted acetonitrile-0.1% phosphoric acid with gradient elution at the flow rate of 1.0 mL·min^-1. The detection wave length was set at 254 nm. HPLC fingerprints of 24 batches of Platycladi Cacumen were established by using the Similarity Evaluation System of TCM Chromatographic Fingerprints (2012 edition), and the common peaks were determined in combination with the spectra of mixed control. SPSS 25.0 software was used for cluster analysis; Simca-P software was used for principal component analysis and partial least squares discriminant analysis; the differential components affecting the quality were screened.

Results  There were 13 common peaks in the fingerprint of Platycladi Cacumen. Compared with the control fingerprint, the similarity of the 23 batches of herbs was greater than 0.92 except for the S2 batch. Four chromatographic peaks were identified, which were myricitrin, quercitri, isoquercitrin and amentoflavone. The results of cluster analysis showed that 24 batches of Platycladi Cacumen could be clustered into two categories. S1, S3-S24 were clustered into one class. The medicinal materials from the same origin had great differences, and the medicinal materials from different origins also had similarities; S2 was clustered into one class, which was Sabina chinensis. The results of principal component analysis showed that the cumulative contribution rate of the six principalcomponents was 88.412%, which could reflect most of the information of the original chromatographic peak. Partial least squares discriminant analysis showed that 5 components were selected ,which were the landmark components of 24 batches of medicinal materials to produce differences.

Conclusion  Established HPLC fingerprint is simple and accurate. Combined with chemical pattern recognition, it can be used for the quality control of Platycladi Cacumen. Five components such as peak 8 are the differential components affecting the quality of Platycladi Cacumen.

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