Author
ZHAO, YANG - University Of Maryland | |
NIU, YUGE - University Of Maryland | |
XIE, ZHUOHONG - University Of Maryland | |
SHI, HAIMING - Shanghai Jiaotong University | |
Chen, Pei | |
YU, LIANGLI (LUCY) - University Of Maryland |
Submitted to: Analytica Chimica Acta
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 7/3/2013 Publication Date: 3/3/2013 Citation: Zhao, Y., Niu, Y., Xie, Z., Shi, H., Chen, P., Yu, L. 2013. Differentiation of leaf and whole-plant samples of di- and tetraploid Gynostemma pentaphyllum (Thunb.) Makino using flow-injection mass spectrometric(FIMS) fingerprinting method combined with chemometric approaches. Analytica Chimica Acta. 5:1288-1297. Interpretive Summary: In the present study, a flow-injection mass spectrometry (FIMS) fingerprinting method combined with chemometric analyses for quality assessment of di- and tetraploid leaf and whole-plant Gynostemma. pentaphyllum (Thunb.) Makino samples was investigated. A rapid method based on FIMS was used to generate fingerprints for four different types of G. pentaphyllum samples. Principal component analysis (PCA) and partial least square discriminatory analysis (PLS-DA) were performed to analyze the fingerprints. The results show that the four different types of G. pentaphyllum samples could be efficiently differentiated in less than 2 min. Furthermore, PLS-DA loading plots revealed 11 characteristic ions that could be used to classify different types of G. pentaphyllum samples. Technical Abstract: In the present study, the feasibility and advantages of employing a flow-injection mass spectrometry (FIMS) fingerprinting method combined with chemometric analyses for quality assessment of di- and tetraploid leaf and whole-plant Gynostemma. pentaphyllum (Thunb.) Makino samples were investigated for the first time. A rapid method based on FIMS was applied to generate spectrometric fingerprints of extracts from four different types of G. pentaphyllum samples. Chemometric approaches including principal component analysis (PCA) and partial least square discriminatory analysis (PLS-DA) were performed. The results show that four different types of G. pentaphyllum samples could be excellently classified and efficiently differentiated in less than 2 min. Furthermore, PLS-DA loadings plot revealed 11 characteristic ions that were the most distinct variables for classification of different types of G. pentaphyllum samples. |