Title:TLC Identification and UPLC-Orbitrap-MS/MS Profiling Chemical Constituents of Chaenomeles sinensis and Chaenomeles speciosa Aided by Chemometrics Approaches
Volume: 22
Issue: 7
Author(s): Jisheng Huang, Qiong Wang, Guo-Chu Shang, Na Li, Weiying Lu, Zeng-Lai Xu*Zhihong Cheng*
Affiliation:
- Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing 210014, China
- Jiangsu Key Laboratory for Conservation and Utilization of Plant Resources, Nanjing 210014, China
- Department of Natural Medicine, School of Pharmaceutical Sciences, Fudan University, Shanghai 201203, China
Keywords:
Chaenomeles sinensis, Chaenomeles speciosa, chemometrics, UPLC-Orbitrap-MS, 3-O-acetylursolic acid, TLC identification.
Abstract:
Introduction: Chaenomeles sinensis and C. speciosa are two closely related plant species.
The confusion or adulteration between the two species is a common occurrence in the herbal market.
Method: A specific TLC method was established to distinguish C. speciosa from C. sinensis. Furthermore,
a new UPLC-Orbitrap-MS/MS method was developed for their classification. This method
entailed analyzing massive MS data from Chaenomeles species, which were processed using a
self-designed VBA program. The classification was facilitated by three chemometric approaches.
Results: 3-O-Acetylursolic acid was discovered, separated, and identified from C. speciosa as the
unique chemical marker. A TLC identification test was thus established to discriminate between
these two species using this marker. All three chemometric models demonstrated robust classification
of 20 Chaenomeles samples. Subsequent structural profiling of chemical compositions in
Chaenomeles species was accomplished.
Discussion: Most of the identified compounds included triterpenoids, with nine compounds common
to both species. TLC and UPLC-MS/MS methods were established for differentiating C. speciosa
from C. sinensis.
Conclusion: The present study also introduces an integrated analytical workflow that merges rapid
TLC prescreening with high-resolution UPLC-MS/MS fingerprinting and chemometric modelling,
enabling unequivocal discrimination of phylogenetically proximate plant species.
