Color discrimination and gas chromatography-mass spectrometry fingerprint based on chemometrics analysis for the quality evaluation of Schizonepetae Spica

PLoS One. 2020 Jan 7;15(1):e0227235. doi: 10.1371/journal.pone.0227235. eCollection 2020.

Abstract

Schizonepetae Spica (SS), the dried spike of Schizonepeta tenuifolia Briq., is a traditional Chinese medicinal herb. According to the color of persistent calyx, SS is categorized into two classes: the yellowish-green-type and the brownish-type. Based on the chemometrics analysis of gas chromatography-mass spectrometry (GC-MS), a novel model of identifying and evaluating the quality of SS in different colors was constructed for the first time in this work. 20 batches SS samples of different colors were collected and used to extract essential oils. The average essential oils yield of SS in yellowish-green color was significantly higher than that of SS in brownish color from the same origin (p<0.05). The GC-MS fingerprints of 20 batches SS samples whose correlation coefficients were over 0.964 demonstrated SS samples were consistent to some extent in spite of slightly different chemical indexes. A total of 39 common volatiles compounds were identified. Hierarchical clustering analysis (HCA), principal component analysis (PCA) and partial least-squares discriminate analysis (PLS-DA) were developed to distinguish SS samples characterized by different colors. Consistent results were obtained to show that SS samples could be successfully grouped according to their color. Finally, 4,5,6,7-tetrahydro-3,6-dimethyl-benzofuran and pulegone were detected as the key variables for discriminating SS samples of different colors and for quality control. The obtained results proved that SS of good quality were often yellowish-green and those of poor quality were often brownish.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Color
  • Discriminant Analysis
  • Drugs, Chinese Herbal / analysis*
  • Drugs, Chinese Herbal / standards
  • Gas Chromatography-Mass Spectrometry / methods*
  • Lamiaceae / chemistry*
  • Oils, Volatile / analysis
  • Oils, Volatile / isolation & purification
  • Plant Components, Aerial / chemistry
  • Principal Component Analysis
  • Quality Control*

Substances

  • Drugs, Chinese Herbal
  • Oils, Volatile

Grants and funding

This work was supported by the sixth batch of National Academic Experience Inheritance Project of Chinese Medicine Experts (No. 176-2017-XMZC-0166-01).