Simultaneous determination and difference evaluation of 14 ginsenosides in Panax ginseng roots cultivated in different areas and ages by high-performance liquid chromatography coupled with triple quadrupole mass spectrometer in the multiple reaction-monitoring mode combined with multivariate statistical analysis

Yang Xiu,Xue Li,Xiuli Sun,Dan Xiao,Rui Miao,Huanxi Zhao,Shuying Liu 고려인삼학회 2019 Journal of Ginseng Research Vol.43 No.4

Background: Ginsenosides are not only the principal bioactive components but also the important indexes to the quality assessment of Panax ginseng Meyer. Their contents in cultivated ginseng vary with the growth environment and age. The present study aimed at evaluating the significant difference between 36 cultivated ginseng of different cultivation areas and ages based on the simultaneously determined contents of 14 ginsenosides. Methods: A high-performance liquid chromatography (HPLC) coupled with triple quadrupole mass spectrometer (MS) method was developed and used in the multiple reaction-monitoring (MRM) mode (HPLC-MRM/MS) for the quantitative analysis of ginsenosides. Multivariate statistical analysis, such as principal component analysis and partial least squares-discriminant analysis, was applied to discriminate ginseng samples of various cultivation areas and ages and to discover the differentially accumulated ginsenoside markers. Results: The developed HPLC-MRM/MS method was validated to be precise, accurate, stable, sensitive, and repeatable for the simultaneous determination of 14 ginsenosides. It was found that the 3- and 5-yrold ginseng samples were differentiated distinctly by all means of multivariate statistical analysis, whereas the 4-yr-old samples exhibited similarity to either 3- or 5-yr-old samples in the contents of ginsenosides. Among the 14 detected ginsenosides, Rg1, Rb1, Rb2, Rc, 20(S)-Rf, 20(S)-Rh1, and Rb3 were identified as potential markers for the differentiation of cultivation ages. In addition, the 5-yr-old samples were able to be classified in cultivation area based on the contents of ginsenosides, whereas the 3- and 4-yr-old samples showed little differences in cultivation area. Conclusion: This study demonstrated that the HPLC-MRM/MS method combined with multivariate statistical analysis provides deep insight into the accumulation characteristics of ginsenosides and could be used to differentiate ginseng that are cultivated in different areas and ages.

Simultaneous determination and difference evaluation of 14 ginsenosides in Panax ginseng roots cultivated in different areas and ages by high-performance liquid chromatography coupled with triple quadrupole mass spectrometer in the multiple reaction-moni

Xiu, Yang,Li, Xue,Sun, Xiuli,Xiao, Dan,Miao, Rui,Zhao, Huanxi,Liu, Shuying The Korean Society of Ginseng 2019 Journal of Ginseng Research Vol.43 No.4

Background: Ginsenosides are not only the principal bioactive components but also the important indexes to the quality assessment of Panax ginseng Meyer. Their contents in cultivated ginseng vary with the growth environment and age. The present study aimed at evaluating the significant difference between 36 cultivated ginseng of different cultivation areas and ages based on the simultaneously determined contents of 14 ginsenosides. Methods: A high-performance liquid chromatography (HPLC) coupled with triple quadrupole mass spectrometer (MS) method was developed and used in the multiple reaction-monitoring (MRM) mode (HPLC-MRM/MS) for the quantitative analysis of ginsenosides. Multivariate statistical analysis, such as principal component analysis and partial least squares-discriminant analysis, was applied to discriminate ginseng samples of various cultivation areas and ages and to discover the differentially accumulated ginsenoside markers. Results: The developed HPLC-MRM/MS method was validated to be precise, accurate, stable, sensitive, and repeatable for the simultaneous determination of 14 ginsenosides. It was found that the 3- and 5-yr-old ginseng samples were differentiated distinctly by all means of multivariate statistical analysis, whereas the 4-yr-old samples exhibited similarity to either 3- or 5-yr-old samples in the contents of ginsenosides. Among the 14 detected ginsenosides, Rg1, Rb1, Rb2, Rc, 20(S)-Rf, 20(S)-Rh1, and Rb3 were identified as potential markers for the differentiation of cultivation ages. In addition, the 5-yr-old samples were able to be classified in cultivation area based on the contents of ginsenosides, whereas the 3- and 4-yr-old samples showed little differences in cultivation area. Conclusion: This study demonstrated that the HPLC-MRM/MS method combined with multivariate statistical analysis provides deep insight into the accumulation characteristics of ginsenosides and could be used to differentiate ginseng that are cultivated in different areas and ages.

Stability criterion and its calculation for sail-assisted ship

Hu, Yihuai,Tang, Juanjuan,Xue, Shuye,Liu, Shewen The Society of Naval Architects of Korea 2015 International Journal of Naval Architecture and Oc Vol.7 No.1

Stability criterion and its calculation are the crucial issue in the application of sail-assisted ship. However, there is at present no specific criterion and computational methods for the stability of sail-assisted ship. Based on the stability requirements for seagoing ships, the stability criterion of the sail-assisted ships is suggested in this paper. Furthermore, how to calculate the parameters and determine some specific coefficients for the ship stability calculation, as well as how to redraw stability curve are also discussed in this paper. Finally, to give an illustration, the proposed method is applied on a sail assisted-ship model with comments and recommendations for improvement.

Dual-Encoded Features from Both Spatial and Curvelet Domains for Image Smoke Recognition

( Feiniu Yuan ),( Tiantian Tang ),( Xue Xia ),( Jinting Shi ),( Shuying Li ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.4

Visual smoke recognition is a challenging task due to large variations in shape, texture and color of smoke. To improve performance, we propose a novel smoke recognition method by combining dual-encoded features that are extracted from both spatial and Curvelet domains. A Curvelet transform is used to filter an image to generate fifty sub-images of Curvelet coefficients. Then we extract Local Binary Pattern (LBP) maps from these coefficient maps and aggregate histograms of these LBP maps to produce a histogram map. Afterwards, we encode the histogram map again to generate Dual-encoded Local Binary Patterns (Dual-LBP). Histograms of Dual-LBPs from Curvelet domain and Completed Local Binary Patterns (CLBP) from spatial domain are concatenated to form the feature for smoke recognition. Finally, we adopt Gaussian Kernel Optimization (GKO) algorithm to search the optimal kernel parameters of Support Vector Machine (SVM) for further improvement of classification accuracy. Experimental results demonstrate that our method can extract effective and reasonable features of smoke images, and achieve good classification accuracy.

Stability criterion and its calculation for sail-assisted ship

Yihuai Hu,Juanjuan Tang,Shuye Xue,Shewen Liu 대한조선학회 2015 International Journal of Naval Architecture and Oc Vol.7 No.1

Stability criterion and its calculation are the crucial issue in the application of sail-assisted ship. However, there is at present no specific criterion and computational methods for the stability of sail-assisted ship. Based on the stability requirements for seagoing ships, the stability criterion of the sail-assisted ships is suggested in this paper. Furthermore, how to calculate the parameters and determine some specific coefficients for the ship stability calculation, as well as how to redraw stability curve are also discussed in this paper. Finally, to give an illustration, the proposed method is applied on a sail assisted-ship model with comments and recommendations for improvement.

Differentiation and identification of ginsenoside structural isomers by two-dimensional mass spectrometry combined with statistical analysis

Yang Xiu,Huanxi Zhao,Xiuli Sun,Xue Li,Shuying Liu 고려인삼학회 2019 Journal of Ginseng Research Vol.43 No.3

Background: In the current phytochemical research on ginseng, the differentiation and structural identificationof ginsenosides isomers remain challenging. In this paper, a two-dimensional mass spectrometry(2D-MS) method was developed and combined with statistical analysis for the directdifferentiation, identification, and relative quantification of protopanaxadiol (PPD)-type ginsenosideisomers. Methods: Collision-induced dissociation was performed at successive collision energy values to producedistinct profiles of the intensity fraction (IF) and ratio of intensity (RI) of the fragment ions. To amplifythe differences in tandem mass spectra between isomers, IF and RI were plotted against collision energy. The resulting data distributions were then used to obtain the parameters of the fitted curves, which wereused to evaluate the statistical significance of the differences between these distributions via the unpairedt test. Results: A triplet and two pairs of PPD-type ginsenoside isomers were differentiated and identified bytheir distinct IF and RI distributions. In addition, the fragmentation preference of PPD-type ginsenosideswas determined on the basis of the activation energy. The developed 2D-MS method was also extendedto quantitatively determine the molar composition of ginsenoside isomers in mixtures of biotransformationproducts. Conclusion: In comparison with conventional mass spectrometry methods, 2D-MS provides more directinsights into the subtle structural differences between isomers and can be used as an alternativeapproach for the differentiation of isomeric ginsenosides and natural products.

Differentiation and identification of ginsenoside structural isomers by two-dimensional mass spectrometry combined with statistical analysis

Xiu, Yang,Ma, Li,Zhao, Huanxi,Sun, Xiuli,Li, Xue,Liu, Shuying The Korean Society of Ginseng 2019 Journal of Ginseng Research Vol.43 No.3

Background: In the current phytochemical research on ginseng, the differentiation and structural identification of ginsenosides isomers remain challenging. In this paper, a two-dimensional mass spectrometry (2D-MS) method was developed and combined with statistical analysis for the direct differentiation, identification, and relative quantification of protopanaxadiol (PPD)-type ginsenoside isomers. Methods: Collision-induced dissociation was performed at successive collision energy values to produce distinct profiles of the intensity fraction (IF) and ratio of intensity (RI) of the fragment ions. To amplify the differences in tandem mass spectra between isomers, IF and RI were plotted against collision energy. The resulting data distributions were then used to obtain the parameters of the fitted curves, which were used to evaluate the statistical significance of the differences between these distributions via the unpaired t test. Results: A triplet and two pairs of PPD-type ginsenoside isomers were differentiated and identified by their distinct IF and RI distributions. In addition, the fragmentation preference of PPD-type ginsenosides was determined on the basis of the activation energy. The developed 2D-MS method was also extended to quantitatively determine the molar composition of ginsenoside isomers in mixtures of biotransformation products. Conclusion: In comparison with conventional mass spectrometry methods, 2D-MS provides more direct insights into the subtle structural differences between isomers and can be used as an alternative approach for the differentiation of isomeric ginsenosides and natural products.