Zheng Xiang1, Xian-Qin Wang, Xiao-Jun Cai, Su Zeng. 1. Department of Pharmaceutical Analysis and Drug Metabolism, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, People's Republic of China. xiangzheng1978@yahoo.cn
Abstract
INTRODUCTION: Metabonomic analysis is an important molecular phenotyping method for characterising plant ecotypic variations; hence, it may become a powerful tool for quality control and discrimination of traditional Chinese medicine (TCM). OBJECTIVE: To discriminate and assess the quality of Curcuma phaeocaulis, C. kwangsiensis and C. wenyujin from different ecotypes. The identification of the compositions of essential oils from the three Curcuma species was included in this study. METHODOLOGY: Metabolomics analysis was carried out on all samples by gas chromatography-mass spectrometry (GC-MS) coupled with multivariate statistical analysis. Characterisation of phytochemicals in essential oils was performed by automated matching to the MS library and comparison of their mass spectra (NIST05 database). RESULTS: Principal component analysis (PCA) effectively distinguished the samples from different species and ecotypes. Partial least squares discrimination analysis (PLS-DA) was successfully employed in classifying the GC-MS data of authentic, commercial and introduction cultivation samples. Furthermore, the components contributing significantly to the discrimination, namely curzerenone, germacrone, curdione and epicurzerenone, were screened by PCA and PLS-DA loading plots and further can be used as chemical markers for discrimination and quality control among different groups of samples.
INTRODUCTION: Metabonomic analysis is an important molecular phenotyping method for characterising plant ecotypic variations; hence, it may become a powerful tool for quality control and discrimination of traditional Chinese medicine (TCM). OBJECTIVE: To discriminate and assess the quality of Curcuma phaeocaulis, C. kwangsiensis and C. wenyujin from different ecotypes. The identification of the compositions of essential oils from the three Curcuma species was included in this study. METHODOLOGY: Metabolomics analysis was carried out on all samples by gas chromatography-mass spectrometry (GC-MS) coupled with multivariate statistical analysis. Characterisation of phytochemicals in essential oils was performed by automated matching to the MS library and comparison of their mass spectra (NIST05 database). RESULTS: Principal component analysis (PCA) effectively distinguished the samples from different species and ecotypes. Partial least squares discrimination analysis (PLS-DA) was successfully employed in classifying the GC-MS data of authentic, commercial and introduction cultivation samples. Furthermore, the components contributing significantly to the discrimination, namely curzerenone, germacrone, curdione and epicurzerenone, were screened by PCA and PLS-DA loading plots and further can be used as chemical markers for discrimination and quality control among different groups of samples.