Quality control and discrimination of Pericarpium Citri Reticulatae and Pericarpium Citri Reticulatae Viride based on high-performance liquid chromatographic fingerprints and multivariate statistical analysis

• Published in: Analytica chimica acta Vol. 588; no. 2; pp. 207 - 215
• Main Authors: Yi, Lun-zhao, Yuan, Da-lin, Liang, Yi-zeng, Xie, Pei-shan, Zhao, Yu
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 11.04.2007; Elsevier
• Subjects: Analytical chemistry; Chemistry; Chromatographic methods and physical methods associated with chromatography; Chromatography, High Pressure Liquid - methods; Citrus - chemistry; Drugs, Chinese Herbal; Exact sciences and technology; Fingerprint; High-performance liquid chromatography–diode array detection; Least-Squares Analysis; Multivariate Analysis; Other chromatographic methods; Partial least squares-linear discrimination analysis; Pericarpium Citri Reticulatae; Pericarpium Citri Reticulatae Viride; Principal component analysis; Quality Control; Pericarpium Citri Reticulatae; Partial least squares-linear discrimination analysis; Fingerprint; High-performance liquid chromatography–diode array detection; Pericarpium Citri Reticulatae Viride; Principal component analysis; Correlation coefficient; Statistical analysis; HPLC chromatography; High-performance liquid chromatography-diode array detection; Marker; Multivariate analysis; PLS regression; Fingerprint method; Quality control; Pericarp; Diode array
• ISSN: 0003-2670; 1873-4324
• DOI: 10.1016/j.aca.2007.02.012

High-performance liquid chromatographic (HPLC) fingerprints of Pericarpium Citri Reticulatae (PCR) and Pericarpium Citri Reticulatae Viride (PCRV) were firstly measured for deliberately collected 39 authentic samples and 21 commercial samples. Both correlation coefficients of similarity for chromatograms and absolute peak areas of characteristic compounds were calculated for quantitative expression of the HPLC fingerprints. After principal component analysis (PCA) successfully distinguished the ‘mixed peels’ samples from authentic samples, partial least squares-linear discrimination analysis (PLS-LDA) was then effectively applied to class separation between authentic PCR and PCRV. Furthermore, the unequivocally determined compounds, hesperidin, nobiletin and tangeretin, were screened out by loadings plots of PCA and PLS-LDA. The results indicated that they could be used as chemical markers for discrimination among different groups of samples. The proposed method shows an efficient strategy for quality control of PCR and PCRV, which cannot only distinguish the ‘mixed peels’ but also discriminate authentic PCR and PCRV. This method has potential perspective for quality control of traditional Chinese medicine (TCM).