Discrimination of Pterocephalus hookeri collected at flowering and non-flowering stages using GC-MS-based fatty acid profiling
For a herbal medicine, harvesting at different growth stage affects its quality and efficiency. We hypothesized that fatty acid profiling might be used to discriminate herbal samples according to their growth stages. To test the hypothesis, fatty acids of Pterocephalus hookeri samples collected at the flowering stage (FS) and non-flowering stages (NFS) were characterized and compared using gas chromatography-mass spectrometry (GC-MS) and followed by multivariate statistical analysis. A total of 14 fatty acids were identified and quantified in all the P. hookeri samples. Both the relative and absolute compositions of the 14 fatty acids varied greatly between the FS and NFS groups, suggesting each group has its own fatty acid pattern. Orthogonal partial least squares discriminant analysis (OPLS-DA) and hierarchical clustering analysis (HCA) based on data sets of relative and absolute composition of fatty acids showed that 13 tested samples could be clearly classified into two clusters, in terms of their growth stages. More importantly, α-linolenic acid, a plant-derived n-3 polyunsaturated fatty acid (PUFA), was identified as the potential fatty acid biomarker for its greatest contribution to the group’s separation. In addition, to evaluate the quality of P. hookeri at the FS and NFS, oleanolic acid (OA) and ursolic acid (UA) were determined by HPLC, as described in the Chinese Pharmacopoeia (version 2010). A higher total concentration of OA and UA could be found in the P. hookeri samples at the flowering stage, which was suggested to be a better quality. These findings demonstrated that GC-MS-based fatty acid profiling, coupled with multivariate statistical analysis, provides a reliable platform to discriminate the herb collected at different growth stages, which is helpful for ensuring its efficacy.