2126 Jing Han Pao Li Wensheng Cai Xueguang Shao Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), State Key Laboratory of Medicinal Chemical Biology, and Research Center for Analytical Sciences, College of Chemistry, Nankai University, Tianjin, China Received April 10, 2014 Revised May 12, 2014 Accepted May 17, 2014
J. Sep. Sci. 2014, 37, 2126–2130
Research Article
Fast determination of ginsenosides in ginseng by high-performance liquid chromatography with chemometric resolution Ginseng is a well-known traditional Chinese medicinal herb, and ginsenosides are its major active components. A method for the fast determination of ginsenosides in ginseng samples by high-performance liquid chromatography was developed and used for the quantitative analysis of four ginsenosides in three different ginseng samples. In this method, instead of time-consuming gradient elution, isocratic elution was used to speed up the analysis. Under strong isocratic elution, all the ginsenosides are eluted in 2.3 min. Although the measured signal is composed of overlapped peaks with the interferences and background, the signal of ginsenosides can be extracted by chemometric resolution. A non-negative immune algorithm was employed to obtain the chromatographic information of the target components from the data. Compared with conventional chemometric approaches, the method can perform the extraction for one-dimensional overlapping signals. The method was validated by the determination of four ginsenosides in three different ginseng samples. The recoveries of the spiked samples were in the range of 94.08–107.3%. Keywords: chemometrics / ginsenosides / high-performance liquid chromatography / isocratic elution / non-negative immune algorithm DOI 10.1002/jssc.201400403
1 Introduction Ginseng has been one of the most popular medicinal herbs in China for thousands of years and has gained recognition over the world in the past few decades. All species of ginseng contain common constituents including ginsenosides, polysaccharides, polyynes, flavonoids, volatile oils, amino acids, polyacetylenic alcohols, vitamins, and fatty acids [1], among which ginsenosides are known as the major bioactive ingredients for their therapeutic effects and considered as quality control markers of ginseng [2]. More than 40 ginsenosides have been identified in different ginseng samples. Ginsenosides are steroid compounds and their pharmacological actions have been found. For example, ginsenoside Rb1 , the major component in American ginseng, can increase the Correspondence: Professor Xueguang Shao, College of Chemistry, Nankai University, Tianjin300071, P. R. China E-mail: [email protected] Fax: +86-22-23502458
Abbreviations: CFA, chemical factor analysis; DAD, diode array detector; HELP, heuristic evolving latent projections; IA, immune algorithm; ITTFA, iterative target transformation factor analysis; EFA, evolving factor analysis; ELSD, evaporative light scattering detector; MCR-ALS, multivariate curve resolution-alternating least squares; NNIA, non-negative immune algorithm; R, correlation coefficient; SFA, subwindow factor analysis; WFA, window factor analysis; WT, wavelet transform; TFA, target factor analysis C 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
synthesis and release of acetylcholine and improve memory. Ginsenoside Rb2 plays an important role in promoting the synthesis of DNA and RNA, scavenging free radicals, and improving myocardial ischemia. Ginsenoside Rg2 can effectively cure coronary heart disease, myocardial ischemia, and hypoxia, and Ginsenoside Rc can inhibit cancer cell function, etc. [3, 4]. During the past few decades, researchers have developed many methods for the identification and quantification of ginsenosides in ginseng and related products. The common techniques used for the analysis of ginsenosides include TLC [5], GC [6], HPLC [7–13], CE [14], and NMR spectroscopy [15]. Among these techniques, HPLC with various detectors, such as diode array detector (DAD) [7, 8], evaporative light scattering detector (ELSD) [9, 10], fluorescence [11], and MS [12, 13], were most commonly used. However, the method still suffers from a few disadvantages such as peak overlap, baseline drift, and long separation time. Therefore, more efficient and accurate analytical methods are still necessary to be developed. Chemometrics provides new opportunities for analyzing complex overlapping signals, and a variety of chemometric methods have been developed for multicomponent signal resolution issues. Methods based on chemical factor analysis (CFA) have been widely employed, for example, evolving factor analysis (EFA) [16], window factor analysis (WFA) Colour Online: See the article online to view Figs. 2–4 in colour. www.jss-journal.com
Liquid Chromatography
J. Sep. Sci. 2014, 37, 2126–2130
[17], heuristic evolving latent projections (HELP) [18, 19], subwindow factor analysis (SFA) [20], target factor analysis (TFA) [21], and iterative target transformation factor analysis (ITTFA) [22–24]. These methods have demonstrated their efficiency in analyzing the samples with complex interference such as traditional Chinese herbal medicine and metabolomic samples [25, 26]. On the other hand, multivariate curve resolution-alternating least squares (MCRALS) [27, 28] has been proved powerful in the analysis of the environmental and biological samples with complex interference matrix [29, 30]. In our previous works, wavelet transform (WT) [31, 32] was developed for enhancing the resolution of analytical signals, and an immune algorithm (IA) [33, 34] was proposed for extracting the useful information from multicomponent complex signals. IA has been developed for resolving overlapping signals in HPLC, spectroscopy, and GC–MS [33–39]. Compared with MCR-ALS, IA extracts information of each component from the total signal by projection and subtraction with the help of the provided standard signals of all the possible components. In primary IA, therefore, the information of all the components possibly contained in the analyzed sample must be provided. For retrieving the information of a specific component from an overlapping signal, non-negative immune algorithm (NNIA) was proposed, which has been proved as an efficient way for the determination of a component of interest in a complex sample [37–39]. In this paper, a method for the fast determination of ginsenosides in ginseng samples by HPLC and chemometric resolution was developed. In the method, the pretreatment of samples was simplified, and isocratic elution was used to speed up the separation. For extracting the chromatographic information of the target components in the overlapping signal, NNIA was applied to the quantitative analysis of the ginsenosides, because the method can extract the information of a component of interest in the presence of unknown interferences and perform the extraction for one-dimensional data.
2 Materials and methods 2.1 Materials and reagents Standards for ginsenosides Rb1 , Rb2 , Rc, and Rg2 (98%) were obtained from Aladin Reagent (Beijing, China). Methanol (HPLC grade) was used to extract the ginsenosides, and acetonitrile (HPLC grade) and distilled water were used for preparing the mobile phase.
2.2 Samples Ginseng samples were purchased from local pharmacies. They were dried in an oven and grounded into fine powder (100 mesh). A 2 g sample powder was weighed into a filter C 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
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cartridge and Soxhlet extracted with 200 mL 80% methanol for 2 h, and the extraction was repeated for three times. The extract was concentrated by rotary evaporation to 10 mL, then filtered with 0.45 m membrane, and stored at 4⬚C for HPLC analysis.
2.3 HPLC analyses The chromatographic system consists of a Waters 1525 binary pump and a Waters 2996 photodiode array detector (Milford, MA, USA). C18 column (Pico·tak, 4 m, 3.9 mm × 150 mm, Waters, USA) was used for separation. The DAD was operated between 210 and 400 nm. The mobile phase was composed of acetonitrile (solvent A) and distilled water (solvent B). For fast analysis of the sample, an isocratic elution (A/B = 3.4:6.6) was used. The flow rate was 1.0 mL/min and the injection volume was 20 L. For comparison, conventionally used gradient elution was used for investigating the ingredients of ginsenosides in ginseng samples referring to the reported methods [40, 41]. The results obtained by gradient elution were used as the standard to evaluate the proposed method. Gradient elution conditions were as follows: 0–5 min, 21% A; 5–28 min, 21– 30% A; 28–45 min, 30–42% A; 45–55 min, 42–90% A; 55–70 min, 90–21% A.
2.4 Chemometric calculations For HPLC–DAD, the signal can be described as an m × n two-way data matrix, where m is the number of retention time and n is the number of wavelength recorded in the spectral information. The purpose of IA is to subtract the signal of each component from an overlapping signal iteratively [33–39]. The measured signal of a mixture (or a sample) and the standard signals of the components are taken as the input and IA iteratively subtracts the signal of each component from the total signal until no signal of the components can be extracted. However, IA cannot correctly extract the information of only one component. Therefore, NNIA was proposed with a negative correction operation. The essence of NNIA is to correct the negative values caused by the extra signal from the overlapping component when the information of only one component is extracted [36]. The negative correction makes NNIA able to extract the information of the components of interest one by one from the measured signal [37–39]. In this work, chromatographic signals of the four ginsenosides were measured and used as the standard signals of the resolving components, respectively. NNIA was used to extract the information of each component from the measured chromatogram. Therefore, the chromatograms and the relative concentrations of the four ginsenosides can be obtained. www.jss-journal.com
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Figure 1. Chromatogram of a ginseng sample with gradient elution.
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Figure 3. Resolved results by NNIA: the dashed lines are the extracted signal of ginsenosides Rb1 , Rc, Rg2 , and Rb2 ; the solid line is the experimental signal; the dotted line is the sum of the extracted signals and the curve is the residual.
3 Results and discussion 3.1 Comparison with conventional method In order to compare the difference between the conventional gradient elution method and the fast isocratic elution method, the extract of ginseng was analyzed by each of the two methods. Figure 1 shows the separation of a sample in the case of gradient elution, which takes 31 min for the separation. Four ginsenosides were identified with the help of the standard substances. As shown in Fig. 1, although optimized separation condition was used, conventional gradient elution still suffers from a long separation time and baseline drift. In the fast isocratic elution method, however, a comparatively strong mobile phase was used. Therefore, the separation only needed a 3 min elution as shown in Fig. 2. With the help of the standard substances, the peaks in the retention time region of 0–1.30 min are coexisting ingredients of
Figure 2. Chromatogram of a ginseng sample with isocratic elution. The solid line is the experimental signal; dashed lines are the chromatographic signals of standard ginsenosides.
C 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
ginseng, and the chromatographic profiles of the four ginsenosides are located in the retention time region of 1.31– 2.30 min. It is clear that the peaks are overlapping due to the fast elution. Chemometric resolution must be adopted to obtain the quantitative information of the ginsenosides.
3.2 Extracting the information of the target component For extracting the chromatographic information of the four ginsenosides from the overlapping signal, NNIA was employed. The experimental signal in the retention time region of 1.31–2.30 min, and the chromatographic profiles of the standard ginsenosides were taken as the input, respectively. In the calculation of the resolution, the information of each ginsenoside was resolved independently with the standard
Figure 4. Relationship of the peak areas and concentrations of the four ginsenoside standard samples.
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J. Sep. Sci. 2014, 37, 2126–2130 Table 1. Calibration curves of ginsenosides
Analyte
Calibration curve
Correlation coefficient (R)
Rb1 Rg2 Rc Rb2
Y = 0.5284X – 0.01188 Y = 0.9229X + 0.09958 Y = 0.7428X + 0.02344 Y = 0.5751X + 0.08356
0.9996 0.9997 0.9996 0.9991
profile of the substance. Therefore, the interferences of coexisting components do not affect the resolution. Figure 3 shows the resolved results. The solid line in black shows the total chromatographic profile of the experimental signal and the resolved results of the four ginsenosides (Rb1 , Rc, Rg2 , and Rb2 ) are plotted by the dashed lines in different colors. Furthermore, the dotted line in blue is the sum of the four resolved peaks that can be used to investigate the difference between the experimental and the total resolved signal. The curve in purple shows the residual after the resolution in the Fig. 3, from which the interference information after the resolution can be known. Besides the obvious residual before retention time 1.5 min, a small peak of interference in retention time 1.76–1.95 min can be clearly seen.
3.3 Quantitative determination Quantitative analysis of the four ginsenosides (Rb1 , Rc, Rg2 , and Rb2 ) in three ginseng samples was performed by using the resolved chromatographic profiles. For comparison, the contents of the ginsenosides were also determined by conventional gradient elution with external standard method. Figure 4 shows the external calibration curves plotted with the peak areas (Y) versus concentrations (X, mg/L) and the equations of the curves for the four ginsenosides are listed in Table 1. Table 2 is a summary of the quantitative results obtained by the proposed fast isocratic elution method and conven-
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tional gradient elution method. The results obtained by conventional method were listed in the second column as reference values to evaluate the results obtained by the proposed method, which were listed in the third column of the table. All the results were the mean value of three repeated measurements; RSD is, therefore, listed to show the reproducibility. It is clear that the calculated contents are consistent well with the reference values and the RSD (n = 3) ranges from 0.07 to 3.13%. The results suggest that, with the help of chemometric resolution, the same quantitative results can be obtained by the fast elution measurement. In order to further validate the results of the proposed method, the recoveries obtained by the spiked ginseng samples were calculated and are listed in Table 2. It can be seen that the recoveries range from 94.08 to 107.3%, demonstrating a good accuracy. From the RSD (n = 3) in the fifth column, it can be found that all the values are less than 3.66%, suggesting a very good reproducibility for the quantitative determination.
4 Concluding remarks A method for fast analysis of ginsenosides in ginseng samples was proposed with the help of chemometric resolution. In the method, tedious preprocessing steps were simplified, and the time-consuming gradient elution was replaced by fast isocratic elution. For extracting the quantitative information from the overlapping signals, chemometric resolution by NNIA was adopted. Both the chromatographic profiles and the relative concentration can be obtained in the calculation. The feasibility of the method was proved by analyzing three different ginseng samples. Compared with the quantitative results by conventional separation of 31 min, the same results can be obtained from the rapid separation of 2.3 min. Both the accuracy and the precisions were proved. Therefore, the proposed method may provide an efficient way for fast analysis of multicomponent samples using chromatography.
Table 2. Quantitative results (mg/L) and accuracy of the method
Analyte
Reference RSD (%)
Calculated RSD (%)
Added
Found RSD (%)
Recovery (%)
Rb1
155.9 (1.50) 329.5 (1.19) 130.9 (0.61) 86.11 (0.60) 111.2 (3.18) 68.30 (2.00) 28.30 (0.62) 53.77 (1.58) 64.38 (1.51) 84.08 (0.88) 101.0 (0.63) 47.92 (1.35)
159.2 (1.83) 334.3 (2.29) 137.4 (2.69) 87.91 (3.13) 106.1 (0.41) 65.42 (0.50) 29.31 (0.15) 54.50 (2.88) 63.98 (3.02) 85.14 (0.07) 100.9 (2.96) 49.53 (0.58)
20.00 60.00 70.00 20.00 40.00 60.00 40.00 30.00 20.00 60.00 30.00 120.0
178.2 (2.85) 397.0 (3.66) 203.3 (2.97) 107.4 (2.78) 148.5 (3.11) 129.8 (1.47) 66.94 (2.07) 83.98 (2.79) 84.87 (0.68) 146.4 (1.52) 129.3 (2.95) 169.4 (2.82)
95.00 104.5 94.14 97.45 106.0 107.3 94.08 98.27 104.5 102.1 94.67 99.89
Rc
Rg2
Rb2
C 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
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This study was supported by National Natural Science Foundation of China (No. 21175074). The authors have declared no conflict of interest.
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Research Article
Fast determination of ginsenosides in ginseng by high-performance liquid chromatography with chemometric resolution Ginseng is a well-known traditional Chinese medicinal herb, and ginsenosides are its major active components. A method for the fast determination of ginsenosides in ginseng samples by high-performance liquid chromatography was developed and used for the quantitative analysis of four ginsenosides in three different ginseng samples. In this method, instead of time-consuming gradient elution, isocratic elution was used to speed up the analysis. Under strong isocratic elution, all the ginsenosides are eluted in 2.3 min. Although the measured signal is composed of overlapped peaks with the interferences and background, the signal of ginsenosides can be extracted by chemometric resolution. A non-negative immune algorithm was employed to obtain the chromatographic information of the target components from the data. Compared with conventional chemometric approaches, the method can perform the extraction for one-dimensional overlapping signals. The method was validated by the determination of four ginsenosides in three different ginseng samples. The recoveries of the spiked samples were in the range of 94.08–107.3%. Keywords: chemometrics / ginsenosides / high-performance liquid chromatography / isocratic elution / non-negative immune algorithm DOI 10.1002/jssc.201400403
1 Introduction Ginseng has been one of the most popular medicinal herbs in China for thousands of years and has gained recognition over the world in the past few decades. All species of ginseng contain common constituents including ginsenosides, polysaccharides, polyynes, flavonoids, volatile oils, amino acids, polyacetylenic alcohols, vitamins, and fatty acids [1], among which ginsenosides are known as the major bioactive ingredients for their therapeutic effects and considered as quality control markers of ginseng [2]. More than 40 ginsenosides have been identified in different ginseng samples. Ginsenosides are steroid compounds and their pharmacological actions have been found. For example, ginsenoside Rb1 , the major component in American ginseng, can increase the Correspondence: Professor Xueguang Shao, College of Chemistry, Nankai University, Tianjin300071, P. R. China E-mail: [email protected] Fax: +86-22-23502458
Abbreviations: CFA, chemical factor analysis; DAD, diode array detector; HELP, heuristic evolving latent projections; IA, immune algorithm; ITTFA, iterative target transformation factor analysis; EFA, evolving factor analysis; ELSD, evaporative light scattering detector; MCR-ALS, multivariate curve resolution-alternating least squares; NNIA, non-negative immune algorithm; R, correlation coefficient; SFA, subwindow factor analysis; WFA, window factor analysis; WT, wavelet transform; TFA, target factor analysis C 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
synthesis and release of acetylcholine and improve memory. Ginsenoside Rb2 plays an important role in promoting the synthesis of DNA and RNA, scavenging free radicals, and improving myocardial ischemia. Ginsenoside Rg2 can effectively cure coronary heart disease, myocardial ischemia, and hypoxia, and Ginsenoside Rc can inhibit cancer cell function, etc. [3, 4]. During the past few decades, researchers have developed many methods for the identification and quantification of ginsenosides in ginseng and related products. The common techniques used for the analysis of ginsenosides include TLC [5], GC [6], HPLC [7–13], CE [14], and NMR spectroscopy [15]. Among these techniques, HPLC with various detectors, such as diode array detector (DAD) [7, 8], evaporative light scattering detector (ELSD) [9, 10], fluorescence [11], and MS [12, 13], were most commonly used. However, the method still suffers from a few disadvantages such as peak overlap, baseline drift, and long separation time. Therefore, more efficient and accurate analytical methods are still necessary to be developed. Chemometrics provides new opportunities for analyzing complex overlapping signals, and a variety of chemometric methods have been developed for multicomponent signal resolution issues. Methods based on chemical factor analysis (CFA) have been widely employed, for example, evolving factor analysis (EFA) [16], window factor analysis (WFA) Colour Online: See the article online to view Figs. 2–4 in colour. www.jss-journal.com
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J. Sep. Sci. 2014, 37, 2126–2130
[17], heuristic evolving latent projections (HELP) [18, 19], subwindow factor analysis (SFA) [20], target factor analysis (TFA) [21], and iterative target transformation factor analysis (ITTFA) [22–24]. These methods have demonstrated their efficiency in analyzing the samples with complex interference such as traditional Chinese herbal medicine and metabolomic samples [25, 26]. On the other hand, multivariate curve resolution-alternating least squares (MCRALS) [27, 28] has been proved powerful in the analysis of the environmental and biological samples with complex interference matrix [29, 30]. In our previous works, wavelet transform (WT) [31, 32] was developed for enhancing the resolution of analytical signals, and an immune algorithm (IA) [33, 34] was proposed for extracting the useful information from multicomponent complex signals. IA has been developed for resolving overlapping signals in HPLC, spectroscopy, and GC–MS [33–39]. Compared with MCR-ALS, IA extracts information of each component from the total signal by projection and subtraction with the help of the provided standard signals of all the possible components. In primary IA, therefore, the information of all the components possibly contained in the analyzed sample must be provided. For retrieving the information of a specific component from an overlapping signal, non-negative immune algorithm (NNIA) was proposed, which has been proved as an efficient way for the determination of a component of interest in a complex sample [37–39]. In this paper, a method for the fast determination of ginsenosides in ginseng samples by HPLC and chemometric resolution was developed. In the method, the pretreatment of samples was simplified, and isocratic elution was used to speed up the separation. For extracting the chromatographic information of the target components in the overlapping signal, NNIA was applied to the quantitative analysis of the ginsenosides, because the method can extract the information of a component of interest in the presence of unknown interferences and perform the extraction for one-dimensional data.
2 Materials and methods 2.1 Materials and reagents Standards for ginsenosides Rb1 , Rb2 , Rc, and Rg2 (98%) were obtained from Aladin Reagent (Beijing, China). Methanol (HPLC grade) was used to extract the ginsenosides, and acetonitrile (HPLC grade) and distilled water were used for preparing the mobile phase.
2.2 Samples Ginseng samples were purchased from local pharmacies. They were dried in an oven and grounded into fine powder (100 mesh). A 2 g sample powder was weighed into a filter C 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
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cartridge and Soxhlet extracted with 200 mL 80% methanol for 2 h, and the extraction was repeated for three times. The extract was concentrated by rotary evaporation to 10 mL, then filtered with 0.45 m membrane, and stored at 4⬚C for HPLC analysis.
2.3 HPLC analyses The chromatographic system consists of a Waters 1525 binary pump and a Waters 2996 photodiode array detector (Milford, MA, USA). C18 column (Pico·tak, 4 m, 3.9 mm × 150 mm, Waters, USA) was used for separation. The DAD was operated between 210 and 400 nm. The mobile phase was composed of acetonitrile (solvent A) and distilled water (solvent B). For fast analysis of the sample, an isocratic elution (A/B = 3.4:6.6) was used. The flow rate was 1.0 mL/min and the injection volume was 20 L. For comparison, conventionally used gradient elution was used for investigating the ingredients of ginsenosides in ginseng samples referring to the reported methods [40, 41]. The results obtained by gradient elution were used as the standard to evaluate the proposed method. Gradient elution conditions were as follows: 0–5 min, 21% A; 5–28 min, 21– 30% A; 28–45 min, 30–42% A; 45–55 min, 42–90% A; 55–70 min, 90–21% A.
2.4 Chemometric calculations For HPLC–DAD, the signal can be described as an m × n two-way data matrix, where m is the number of retention time and n is the number of wavelength recorded in the spectral information. The purpose of IA is to subtract the signal of each component from an overlapping signal iteratively [33–39]. The measured signal of a mixture (or a sample) and the standard signals of the components are taken as the input and IA iteratively subtracts the signal of each component from the total signal until no signal of the components can be extracted. However, IA cannot correctly extract the information of only one component. Therefore, NNIA was proposed with a negative correction operation. The essence of NNIA is to correct the negative values caused by the extra signal from the overlapping component when the information of only one component is extracted [36]. The negative correction makes NNIA able to extract the information of the components of interest one by one from the measured signal [37–39]. In this work, chromatographic signals of the four ginsenosides were measured and used as the standard signals of the resolving components, respectively. NNIA was used to extract the information of each component from the measured chromatogram. Therefore, the chromatograms and the relative concentrations of the four ginsenosides can be obtained. www.jss-journal.com
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Figure 1. Chromatogram of a ginseng sample with gradient elution.
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Figure 3. Resolved results by NNIA: the dashed lines are the extracted signal of ginsenosides Rb1 , Rc, Rg2 , and Rb2 ; the solid line is the experimental signal; the dotted line is the sum of the extracted signals and the curve is the residual.
3 Results and discussion 3.1 Comparison with conventional method In order to compare the difference between the conventional gradient elution method and the fast isocratic elution method, the extract of ginseng was analyzed by each of the two methods. Figure 1 shows the separation of a sample in the case of gradient elution, which takes 31 min for the separation. Four ginsenosides were identified with the help of the standard substances. As shown in Fig. 1, although optimized separation condition was used, conventional gradient elution still suffers from a long separation time and baseline drift. In the fast isocratic elution method, however, a comparatively strong mobile phase was used. Therefore, the separation only needed a 3 min elution as shown in Fig. 2. With the help of the standard substances, the peaks in the retention time region of 0–1.30 min are coexisting ingredients of
Figure 2. Chromatogram of a ginseng sample with isocratic elution. The solid line is the experimental signal; dashed lines are the chromatographic signals of standard ginsenosides.
C 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
ginseng, and the chromatographic profiles of the four ginsenosides are located in the retention time region of 1.31– 2.30 min. It is clear that the peaks are overlapping due to the fast elution. Chemometric resolution must be adopted to obtain the quantitative information of the ginsenosides.
3.2 Extracting the information of the target component For extracting the chromatographic information of the four ginsenosides from the overlapping signal, NNIA was employed. The experimental signal in the retention time region of 1.31–2.30 min, and the chromatographic profiles of the standard ginsenosides were taken as the input, respectively. In the calculation of the resolution, the information of each ginsenoside was resolved independently with the standard
Figure 4. Relationship of the peak areas and concentrations of the four ginsenoside standard samples.
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Liquid Chromatography
J. Sep. Sci. 2014, 37, 2126–2130 Table 1. Calibration curves of ginsenosides
Analyte
Calibration curve
Correlation coefficient (R)
Rb1 Rg2 Rc Rb2
Y = 0.5284X – 0.01188 Y = 0.9229X + 0.09958 Y = 0.7428X + 0.02344 Y = 0.5751X + 0.08356
0.9996 0.9997 0.9996 0.9991
profile of the substance. Therefore, the interferences of coexisting components do not affect the resolution. Figure 3 shows the resolved results. The solid line in black shows the total chromatographic profile of the experimental signal and the resolved results of the four ginsenosides (Rb1 , Rc, Rg2 , and Rb2 ) are plotted by the dashed lines in different colors. Furthermore, the dotted line in blue is the sum of the four resolved peaks that can be used to investigate the difference between the experimental and the total resolved signal. The curve in purple shows the residual after the resolution in the Fig. 3, from which the interference information after the resolution can be known. Besides the obvious residual before retention time 1.5 min, a small peak of interference in retention time 1.76–1.95 min can be clearly seen.
3.3 Quantitative determination Quantitative analysis of the four ginsenosides (Rb1 , Rc, Rg2 , and Rb2 ) in three ginseng samples was performed by using the resolved chromatographic profiles. For comparison, the contents of the ginsenosides were also determined by conventional gradient elution with external standard method. Figure 4 shows the external calibration curves plotted with the peak areas (Y) versus concentrations (X, mg/L) and the equations of the curves for the four ginsenosides are listed in Table 1. Table 2 is a summary of the quantitative results obtained by the proposed fast isocratic elution method and conven-
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tional gradient elution method. The results obtained by conventional method were listed in the second column as reference values to evaluate the results obtained by the proposed method, which were listed in the third column of the table. All the results were the mean value of three repeated measurements; RSD is, therefore, listed to show the reproducibility. It is clear that the calculated contents are consistent well with the reference values and the RSD (n = 3) ranges from 0.07 to 3.13%. The results suggest that, with the help of chemometric resolution, the same quantitative results can be obtained by the fast elution measurement. In order to further validate the results of the proposed method, the recoveries obtained by the spiked ginseng samples were calculated and are listed in Table 2. It can be seen that the recoveries range from 94.08 to 107.3%, demonstrating a good accuracy. From the RSD (n = 3) in the fifth column, it can be found that all the values are less than 3.66%, suggesting a very good reproducibility for the quantitative determination.
4 Concluding remarks A method for fast analysis of ginsenosides in ginseng samples was proposed with the help of chemometric resolution. In the method, tedious preprocessing steps were simplified, and the time-consuming gradient elution was replaced by fast isocratic elution. For extracting the quantitative information from the overlapping signals, chemometric resolution by NNIA was adopted. Both the chromatographic profiles and the relative concentration can be obtained in the calculation. The feasibility of the method was proved by analyzing three different ginseng samples. Compared with the quantitative results by conventional separation of 31 min, the same results can be obtained from the rapid separation of 2.3 min. Both the accuracy and the precisions were proved. Therefore, the proposed method may provide an efficient way for fast analysis of multicomponent samples using chromatography.
Table 2. Quantitative results (mg/L) and accuracy of the method
Analyte
Reference RSD (%)
Calculated RSD (%)
Added
Found RSD (%)
Recovery (%)
Rb1
155.9 (1.50) 329.5 (1.19) 130.9 (0.61) 86.11 (0.60) 111.2 (3.18) 68.30 (2.00) 28.30 (0.62) 53.77 (1.58) 64.38 (1.51) 84.08 (0.88) 101.0 (0.63) 47.92 (1.35)
159.2 (1.83) 334.3 (2.29) 137.4 (2.69) 87.91 (3.13) 106.1 (0.41) 65.42 (0.50) 29.31 (0.15) 54.50 (2.88) 63.98 (3.02) 85.14 (0.07) 100.9 (2.96) 49.53 (0.58)
20.00 60.00 70.00 20.00 40.00 60.00 40.00 30.00 20.00 60.00 30.00 120.0
178.2 (2.85) 397.0 (3.66) 203.3 (2.97) 107.4 (2.78) 148.5 (3.11) 129.8 (1.47) 66.94 (2.07) 83.98 (2.79) 84.87 (0.68) 146.4 (1.52) 129.3 (2.95) 169.4 (2.82)
95.00 104.5 94.14 97.45 106.0 107.3 94.08 98.27 104.5 102.1 94.67 99.89
Rc
Rg2
Rb2
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This study was supported by National Natural Science Foundation of China (No. 21175074). The authors have declared no conflict of interest.
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