Objective  To establish the dual-wavelength fingerprints of 10 batches of Pingna honey paste, and combine with chemical pattern recognition methods to provide a basis for its quality control and standard formulation.

Methods  High performance liquid chromatography (HPLC) was performed on a Shim Nex CS C₁₈ chromatographic column (250 mm×4.6 mm, 5 μm), with acetonitrile-0.4% phosphoric acid aqueous solution as the mobile phase under gradient elution. The column temperature was 30 ℃, the flow rate was 1.0 mL/min, the detection wavelengths were 330 nm and 245 nm, and the injection volume was 10 μL. The HPLC chromatograms of 10 batches of Pingna honey paste were analyzed by the Traditional Chinese Medicine Chromatographic Fingerprint Similarity Evaluation System (2012 Edition), and a dual-wavelength fingerprint was established. Then, further clustering analysis, principal component analysis, and orthogonal partial least squares discriminant analysis were performed on the fingerprint spectrum at a wavelength of 330 nm.

Results  The HPLC dual-wavelength (330 nm and 245 nm) fingerprints of 10 batches of Pingna honey paste were indentified, and a total of 13 and 7 common peaks were calibrated. By comparing with the reference substance, 5 components were identified, including caffeic acid, linarin, luteolin, apigenin, and rupestonic acid. The similarity of all samples was greater than 0.9. The results of chemical pattern recognition analysis showed that 10 batches of samples could be divided into 3 categories, and 5 differential components were screened out, including peak 2 (caffeic acid), peak 10, peak 1, peak 3, and peak 6 (linarin).

Conclusion  The dual-wavelength fingerprint spectrum and chemical pattern recognition method established in this study are accurate and reliable, which can provide important data support for the quality standard research of Pingna honey paste.

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