Journal of Analytical Methods in Chemistry
Volume 2015 (2015), Article ID 517402, 7 pages
http://dx.doi.org/10.1155/2015/517402

Research Article

Identification and Quality Assessment of Chrysanthemum Buds by CE Fingerprinting

Xiaoping Xing and Dan Li

Department of Chemical and Biological Engineering College, Yancheng Institute of Technology, Yancheng 224051, China

Received 3 March 2015; Revised 10 April 2015; Accepted 15 April 2015

Academic Editor: Josep Esteve-Romero

Copyright © 2015 Xiaoping Xing and Dan Li. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

A simple and efficient fingerprinting method for chrysanthemum buds was developed with the aim of establishing a quality control protocol based on biochemical makeup. Chrysanthemum bud samples were successively extracted by water and alcohol. The fingerprints of the chrysanthemum buds samples were obtained using capillary electrophoresis and electrochemical detection (CE-ED) employing copper and carbon working electrodes to capture all of the chemical information. 10 batches of chrysanthemum buds were collected from different regions and various factories to establish the baseline fingerprint. The experimental data of 10 batches electropherogram buds by CE were analyzed by correlation coefficient and the included angle cosine methods. A standard chrysanthemum bud fingerprint including 24 common peaks was established, 12 from each electrode, which was successfully applied to identify and distinguish between chrysanthemum buds from 2 other chrysanthemum species. These results demonstrate that fingerprint analysis can be used as an important criterion for chrysanthemum buds quality control.

1. Introduction

Chrysanthemums, colloquially known as mums, are herbaceous perennial flowering plants and have been cultivated for over 3 millennia. Chrysanthemums include more than 3000 varieties [1], including Ammobium alatum, perennial chamomile, Aster novi-belgii, and Calendula officinalis, which come from different regions, flower in different seasons, and may contain different active compounds. Chrysanthemum buds are one of the highest grades of chrysanthemum in use. Chrysanthemum buds are an important component in many traditional Chinese medicine (TCM) formulas [2] for its therapeutic effects, which include antioxidant, anti-inflammatory, antiviral (including HIV), antimutagenic, anticarcinogenic, antihepatotoxic, and antiaging activities [3]. Chrysanthemum buds are also a common health food/supplement used by many consumers [4] for “scattering cold,” “cleaning heat and toxin,” and “brightening eyes,” which are considered beneficial to human health.

Significant amounts of biologically active compounds have been found in chrysanthemum buds that play important roles in human body, mainly including flavonoids, carbohydrate, and essential oils [5]. Among these compounds, chlorogenic acid, luteolin, and glucoside have been confirmed to possess a variety of biological activities [6]. Traditionally, these active components were used to evaluate the quality of raw plant material. However, owing to the fact that there are hundreds of complex active components in chrysanthemum buds, it has been extremely difficult to identify all these substances and carry out quantitative analyses on them individually. What is more, the chemical composition of chrysanthemum buds can differ between different varieties. As a result, it became necessary to develop a new technology to capture the total chemical composition of chrysanthemum buds and to identify chrysanthemum varieties and verify their authenticity.

Fingerprinting is a method to capture total chemical information of herbs by chemical analytical techniques and is displayed as spectrograms, electropherograms, and other graphs. Fingerprint analyses produce a representative “fingerprint” that contains the greatest amount of information possible to accurately represent a sample and distinguish it from others. Fingerprint analysis of medicinal herbs has been the optimal measurement for identifying and assessing the variety and quality of the plants. Fingerprint analysis has been accepted as a strategy for the assessment of herbal medicines for the evaluation of medicinal products for herbal preparations by the U.S. Food and Drug Administration (FDA) [7] and the European Medicines Agency [8]. In China, the former State Drug Administration (SDA) also began to develop fingerprints of raw materials as a standard of quality control in 2000 [9].

Recently, several techniques have been developed which can characterize the nature and chemical composition of substances. HPLC [10] and GC [11], prime techniques used for fingerprint analysis, have high precision, sensitivity, and reproducibility. However, sample preparations, including preconcentration and derivatization, are often time-consuming, complicated, and troublesome. Thin layer chromatography (TLC) [12] is a commonly used technique for screening of herbal liquid extracts. The ultra-performance liquid chromatography (UPLC) [13] approach has some advantages over HPLC, GC, and TLC, including a large decrease in analysis time and solvent consumption, the possibility of obtaining high efficiencies, and the ability to resolve coeluting compounds. However, its drawbacks include increased back-pressure and the availability of only few stable stationary phases.

CE technology has been widely applied to the characterization of diverse samples due to its low cost, minimal sample volume requirement, short analysis time, and high separation efficiency [14–16]. Electrochemical detection (ED) is a commonly used chemical detection method because of the small size of both the detector and control instrumentation and low power demands [17]. CE coupled to electrochemical detection (CE-ED) is a useful technology offering high sensitivity and good selectivity for electroactive analytes. Based on the two main kinds of active compounds in chrysanthemum buds, flavonoids and polysaccharides including the hydroxyl (–OH) groups are electroactive at carbon and copper electrodes, respectively, which suggests that CE-ED is an appropriate method to investigate the chemical fingerprint of chrysanthemum buds.

The purpose of this study is to establish chromatographic fingerprints of chrysanthemum buds by CE-ED analysis. In this analysis, water and alcohol extraction methods will be successively employed to enhance extraction efficiency. Copper and carbon electrodes will be both used to guarantee that the fingerprints produced can encompass the main bioactive compounds. Two distinct chrysanthemum samples will be identified by the utility of the proposed fingerprint.

2. Materials and Methods

2.1. Materials and Reagents

Glucose and fructose were purchased from Sigma (St. Louis, MO, USA). Chlorogenic acid and luteolin were obtained from Shanghai Yuanye (Shanghai, China). Disodium tetraborate decahydrate (Na₂B₄O₇·10H₂O), H₃BO₃, phosphate salts, and sodium hydroxide (NaOH) were obtained from Shanghai Yuanye (Shanghai, China). All reagents were of analytical grade.

Glucose and fructose stock solutions were prepared in deionized water (Yancheng Chunyu Reagent Factory, Jiangsu, China). Chlorogenic acid and luteolin stock solutions were prepared with ethyl alcohol. The concentration of all stock solutions was 0.01 g mL⁻¹. All analytes were diluted to the desired concentration in running buffer for CE analysis.

2.2. Sample Collection and Handling

Twelve batches of chrysanthemum bud samples were purchased from supermarkets in five main cultivation areas located in China (Table 1). The chrysanthemum buds were dried at room temperature and finely ground using a blender (Joyoung Limited by Share Ltd., Shandong, China). The analytes in chrysanthemum buds were extracted as follows.

Table 1: Resource of ten chrysanthemum buds’ sample.

Sample number
Name of sample
Source

1
King of chrysanthemum buds
Hangzhou, Zhejiang

2
Chrysanthemum buds
Huangshan, Anhui

3
Chrysanthemum buds
Sheyang, Jiangsu

4
Chrysanthemum buds
Tongxiang, Zhejiang

5
Chrysanthemum buds
Jiaozuo, Henan

6
Chrysanthemum buds
Linyi, Shandong

7
Chrysanthemum buds
Lin’an, Zhejiang

8
Chrysanthemum buds
Kunming, Yunnan

9
Chrysanthemum buds
Yulin, Guangxi

10
Chrysanthemum buds
Bozhou, Anhui

11
Chrysanthemum morifolium
Hangzhou, Zhejiang

12
Chrysanthemum indicum
Bozhou, Anhui

First, the milled chrysanthemum buds (1 g) were suspended in 40 mL of deionized water and then ultrasonicated for 30 min to lyse the cells. Next, the mixture was heated at 90°C for 30 min to extract the water-soluble compounds. The suspension was cleared by centrifugation at 14800 rpm for 2 min using an Anke TGL-16C centrifuge (Shanghai Anting Instrument Factory, Shanghai, China), and the supernatant was filtered through a 0.22-m membrane to produce the polysaccharide fraction. To obtain the flavonoid fraction, the filtered residue was extracted with 50 mL 95% ethanol solution and ultrasonicated for 30 min. This suspension was centrifuged and stored as above. Before analysis, the samples were diluted with running buffer. All samples were prepared fresh every day.

2.3. Electrode Preparation

In this study, all employed electrodes were made in our laboratory.

A scrap copper wire (25 cm long, 0.3 mm diameter) was sealed into a soft glass capillary (10 cm long) with glue water. The capillary was cut perpendicular to its length to expose the wire at both ends. A copper electrode was used as soon as the glue solidified.

A lead inside a graphite pencil (4 cm long, 0.3 mm diameter) was first burnished and carefully wound with a polished copper wire. Then, the lead was sealed into a soft glass capillary with glue water. Finally, the capillary was cut perpendicular to its length to expose the lead and wire at each end of the capillary. The carbon electrode was used as soon as the glue solidified.

At the start of each experiment, both ends of the copper or carbon electrode were polished with extra fine carborundum paper followed by the sonication in deionized water using KQ-100KDE ultrasonic generator purchased from Kunshan Ultrasonic Instruments Co., Ltd. (Kunshan, China) before being placed in the cell.

2.4. CE-ED Instrument

CE analysis was performed on a laboratory-built CE-ED system [18]. A 30 kV high voltage power supply (Shanghai Institute of Nuclear Research, China) supplied the voltage between the ends of the capillary. The inlet end of the capillary was held at cathodic potential and the outlet end was maintained at ground. The inlet cell was filled with the separation running buffer, and the outlet end was placed in the detection cell filled with detection running buffer. A fused-silica capillary of 25 m (inner diameter) obtained from Hebei Yongnian Factory (Handan, China) was used for the separation. The samples were injected electrokinetically.

The design of the CE-ED system was based on the end-column approach. The working electrode (either copper or carbon) was placed at the outlet of the separation capillary, and detection was carried out in the reservoir containing the grounding electrode for the CE instrument. Before use, the surface of the working electrode was positioned carefully opposite to the capillary outlet using a micropositioner (Shanghai Lianyi Instrument Factory, China). A three-electrode cell system composed of the working electrode, a platinum auxiliary electrode, and a saturated calomel electrode (SCE) was employed along with a BAS LC-3D amperometric detector (Biochemical System, West Lafayette, IN, USA). The electropherograms were processed with the HW-2000 software (Shanghai Qianpu Microsoftware, China).

2.5. CE Analysis

As in previous CE-ED analyses [19], several key factors were investigated to find the optimal separation conditions. The running buffer was selected from Na₂B₄O₇-H₃BO₃, phosphate salts, Na₂B₄O₇-NaOH, and NaOH; pH and the concentration of the running buffer varied from 9 to 13 and from 10 to 50 mM, respectively; separation voltage ranged from 10 to 25 kV; the potential applied to copper working electrode ranged from 0.5 to 0.8 V, and the potential applied to carbon working electrode ranged from 0.8 to 1.1 V.

2.6. Data Analysis

The method was validated by identifying some key known compounds in chrysanthemum buds, such as chlorogenic acid, luteolin, glucose, and fructose. The relative standard deviations (RSDs), linearity, and detection limits of these compounds were calculated to determine the feasibility of this method.

Due to the novelty of fingerprinting analysis, only a few papers have been published on chemometrics [20]. In this study, data were analyzed with the professional software Computer-Aided Similarity Evaluation, which was developed based on chemometrics by the Research Center for the Modernization of Traditional Chinese Medicines (Central South University, Changsha, China). Ten batches of chrysanthemum buds were analyzed to establish the mean chromatograph as a representative standard fingerprint electropherogram. Data was analyzed using included angle cosine [21] and correlation coefficient [22] methods in order to compare their suitability for discriminating between chrysanthemum fingerprints.

The included angle cosine method considers the fingerprint spectrum data as a multidimensional space vector to convert the fingerprint spectrum similarity problem into the similarity between multidimensional vectors. The included angle cosine () is calculated by the following equation:

while the correlation coefficient (), which measures the relationship between the two properties, is calculated by the following equation:

where and are the th elements in the two different electropherograms (namely, and , resp.) and is the number of the elements in the electropherograms. and are the mean values of the elements in electropherograms and , respectively.

2.7. Sample Identification

Under the optimum analysis conditions, Chrysanthemum morifolium and Chrysanthemum indicum obtained from local supermarkets were analyzed by CE-ED. The electropherograms were compared with the standard fingerprint of chrysanthemum buds to distinguish between various chrysanthemums.

3. Results and Discussion

3.1. CE Analysis

In order to achieve good separation of main components and quantify all of the bioactive chemical compounds in chrysanthemum buds, copper and carbon electrodes were utilized as the working electrode to analyze polysaccharides and flavonoids, respectively.

3.1.1. Optimization Condition of CE with Carbon Working Electrode

The carbon electrode was used as the working electrode mainly to analyze flavonoid compounds in chrysanthemum bud samples. Running buffer selection was considered first because of its significant effect on separation. Na₂B₄O₇-NaOH was chosen as the running buffer for its greater elution effect after comparing with the separation efficiency of Na₂B₄O₇-H₃BO₃, phosphate salts, and Na₂B₄O₇-NaOH.

The acidity and concentration of the running buffer also plays a key role in CE due to its effects on the zeta-potential (), the electroosmotic flow (EOF), and the overall charge of the analytes, all of which impact the separation and migration time of the analytes. When the pH of the same running buffer in separation cell and detection cell was lower than 9.89, two standard compounds (chlorogenic acid and luteolin) could not be separated and there were few peaks, demonstrating poor separation efficiency. On the other hand, when the pH of the running buffer was higher than 12, the migration time was over 1 h. So pH 11.25 Na₂B₄O₇-NaOH (including 3.1 × 10⁻³ g mL⁻¹ boric acid ions) was selected as the optimum running buffer, balancing good separation with reasonable separation times.

The potential applied to the working electrode directly affected the sensitivity and detection limit of this method. Separation voltage affects the velocity of the electroosmotic flow and the migration time of the analytes. In the following analyses, the potential applied to the carbon electrode was maintained at 0.95 V, where the background current was not too high, while the signal-to-noise (S/N) ratio was the highest. Moreover, the working electrode demonstrated good stability and high reproducibility at this optimum potential.

The effect of the separation voltage on the migration time of the analytes was also studied. The results show that a higher separation voltage resulted in shorter migration times for all analytes but also resulted in increased baseline noise. In the following analyses, the separation voltage was maintained at 14 V.

3.1.2. Optimization of CE with Copper Working Electrode

The copper electrode was used to analyze polysaccharide compounds in chrysanthemum buds. The optimal condition was selected with the same selection standards as for the carbon electrode. In order to obtain good separation and detection simultaneously [23], NaOH (pH 13.0) was selected as the optimal detection buffer because of the good response of the copper electrode in strong basic solution, and Na₂B₄O₇ (pH 9.24, 7.63 × 10⁻³ g mL⁻¹) was selected as the best separation buffer because it resulted in a good separation efficiency. The optimal potential to the copper working electrode was determined to be 0.67 V, and the optimal separation voltage was determined to be 20 kV.

3.2. Establishing the Fingerprint of Chrysanthemum Buds

Because the similarity analysis determined that the 10 batches of chrysanthemum buds were highly similar, they were used to produce mean electropherograms for chrysanthemum buds using the copper working electrode (Figure 1) and the carbon working electrode (Figure 2). Together, these electropherograms comprise a comprehensive fingerprint of the bioactive compounds in chrysanthemum buds.

Figure 1: Standard fingerprint for chrysanthemum buds obtained from CE with the carbon working electrode. Peak 5: chlorogenic acid; Peak 6: luteolin. Working potential is 0.95 V (versus SCE); running buffer: Na₂B₄O₇-NaOH (pH 11.25, 3.1 × 10⁻³ g mL⁻¹ boric acid ions); separation voltage: 14 kV, inject time: 8 s.

Figure 2: Standard fingerprint for chrysanthemum buds obtained from CE with the copper working electrode. Peak 8: glucose; Peak 11: fructose. Working potential: 0.67 V (versus SCE); separation buffer: Na₂B₄O₇ (pH 9.24, 7.63 × 10⁻³ g mL⁻¹); detection buffer: NaOH (pH 13.0); separation voltage: 20 kV, inject time: 8 s.

3.3. Identification of Markers and Method Validation

Some compounds found in chrysanthemum buds, such as chlorogenic acid, luteolin, glucose, and fructose, were selected as marker compounds to validate this technology. Peaks 8 and 11 in Figure 1 represent glucose and fructose, respectively. Peaks 5 and 6 in Figure 2 represent chlorogenic acid and luteolin, respectively. The reproducibility of the peak current was evaluated by repeatedly injecting a standard solution under the optimum conditions. The RSDs of the migration time were 1.83%, 0.57%, 2.13%, and 1.41%, respectively.

Additionally, a dilution series of standard solutions was also tested to measure the linearity of the current response for each of the four standard analytes. The linearity and detection limits are summarized in Table 2. As predicted, the observed reproducibility and detection limits of the four analytes were satisfactory.

Table 2: Results of the regression analysis on the calibration curves and the detection limits.

Compound
Regression equation¹
Correlation coefficient ()
Linear range (×10⁻⁴ g mL⁻¹)
Detection² limits (10⁻⁷ g mL⁻¹)

Glucose

0.997
0.02–2.0
3.5

Fructose

0.998
0.02–2.0
1.8

Chlorogenic acid

0.995
0.02–2.0
6.2

Luteolin

0.998
0.02–2.0
5.1

y is the peak area; x is the concentration of the analytes (g mL⁻¹).

²The detection limits correspond to the concentrations of the signal-to-noise ratio of 3.

3.4. Common Peaks Selection

Peaks found in all samples were assigned as “common peaks,” standing for the main characteristic compounds and representing the chemical profile of sample. According to the selection criterion of common peaks in Chinese herbs, common peaks were selected as those with a migration time RSD lower than 5% and a minimum relative peak area of less than 0.5%. Ten chrysanthemum bud samples were analyzed by CE with both the copper and carbon electrodes. 12 common peaks were chosen from each of the two CE electropherograms as the common peaks for chrysanthemum buds for a total of 24.

3.5. Similarity Analysis

The similarity of 10 batches of chrysanthemum bud samples from various locations was evaluated by correlation coefficient and the included angle cosine. The similarity between samples was calculated by the correlation coefficient method with the average of all samples as a standard, and the similarities between samples were calculated by the included angle cosine method with the average of all samples taken as a standard. If the value of angle cosine and correlation coefficient from samples are similar with and , the samples are assigned to the same origin.

From the data analysis in Tables 3 and 4, ten chrysanthemum bud samples (numbers 1–10) had high similarity even though the concentration of active compounds among samples was not at the same level. From the results it can be concluded that the ten samples belong to the same species even though they are obtained from different place and different years.

Table 3: Peak area of various samples analyzed by CE with carbon electrode.

Peak
Sample¹

1#
2#
3#
4#
5#
6#
7#
8#
9#
10#
11#
12#

1
1412023
1645374
1663717
1458483
1546122
1354982
1841631
1567651
1103240
1534023
No found
No found

2
907835
851391
813486
921323
923131
921354
835468
947313
994135
903712
No found
No found

3
2149706
2216378
2484610
2462123
2237155
2148461
1975232
2567855
2657165
1956742
1944541
2383874

4
1171446
1942103
1431231
1321330
903493
1579132
913485
1683256
1134902
991324
1076725
959534

5
16923651
18792134
19715642
13544132
18713543
15463449
19738394
18974667
13598120
14792134
6937854
7194685

6
679752
721564
643485
624836
681324
647122
594321
646794
679123
708616
1441354
2273234

7
14524829
15461365
11763465
18741561
13675645
10764475
18467132
19467486
13268785
15679815
10645381
8269314

8
5137047
5464132
5164725
5844154
5132112
5487612
5616912
581361
512641
541341
4251672
4586133

9
2166917
1774315
1843242
2354987
2465135
1949314
1891654
1676312
2546138
1687105
No found
2156515

10
3685649
4013651
4164623
3348971
3254854
3845624
3945215
3521265
3842946
4015689
3498665
3372452

11
4633980
5163435
4831656
4137568
4513981
4861635
5013826
4254682
4821591
4879612
4157674
No found

12
5547956
5312486
5461358
5782923
5978613
5428913
5342381
5138198
6021567
6223365
4978784
5445845

0.997
0.995
0.969
0.957
0.990
0.978
0.996
0.981
0.973
0.976
0.890
0.841

0.998
0.998
0.984
0.977
0.994
0.987
0.997
0.985
0.986
0.986
0.910
0.903

Previous 10 batches (from number 1 to number 10) are real samples to establish the standard fingerprint; numbers 11 and 12 are the real samples to be assessed.

Table 4: Peak area of various samples analyzed by CE-copper electrode.

Peak
Sample

1#
2#
3#
4#
5#
6#
7#
8#
9#
10#
11#
12#

1
3747425
3624777
4358598
6876961
5709162
4521216
4452454
4021416
5601451
4335254
7511364
4679831

2
153880
85758
141249
105365
95080
98623
131639
108698
150123
106415
No found
65264

3
1080579
978309
655783
629236
896236
91636
970861
800012
609357
879412
1064891
501310

4
104520
75693
67969
95421
90413
102576
89563
101233
91975
84489
98699
58956

5
238491
147583
219547
187573
219576
167089
197456
129046
148643
177533
287789
No found

6
149385
237952
288587
189234
190643
289456
190121
188965
159758
189765
159137
251987

7
58153
73624
55581
74285
69210
57459
61361
57868
71698
69124
No found
No found

8
1478427
1881504
1675532
1086598
789865
979853
1376068
1678754
1586985
975097
2457040
1178621

9
2746590
2088749
1286953
2089796
2083654
1875916
2987542
2858155
2074764
3585875
No found
No found

10
268517
361587
291786
301765
369866
308716
345425
222752
357146
291578
368271
407981

11
406312
295709
454106
305136
416918
309572
451986
312476
281461
331653
334586
321786

12
454742
562069
356123
501685
542352
441875
501153
608754
409852
588743
541657
487819

0.976
0.975
0.971
0.978
0.983
0.986
0.989
0.980
0.992
0.960
0.877
0.876

0.983
0.981
0.980
0.980
0.987
0.989
0.992
0.986
0.993
0.973
0.902
0.902

3.6. Application of Standardized Fingerprint for Identification

Fingerprinting analysis can be used to assess the quality of chrysanthemum buds that come from different sources. By examining the relative retention time and the relative peak area of the common peaks in a fingerprint, we can determine whether a raw herb is genuine. But the most important application of fingerprints is that they can be used to separate different chrysanthemum varieties from each other.

Under the optimal analysis conditions, two other chrysanthemum species (Chrysanthemum morifolium and Chrysanthemum indicum) were analyzed by this CE-ED method. By comparing their electropherograms with the standardized fingerprint of chrysanthemum buds (Tables 3 and 4), the distinctive features of each species have been identified. Some of the fingerprint common peaks are not found (carbon peaks 1, 2, 9, and 11; copper peaks 2, 5, 7, and 9) from both species. What is more, similarity analysis demonstrated that these species are significantly different from and , which are considered to be very different by the Chinese Pharmacopoeia Commission and in accordance with the actual varieties we bought from the supermarket.

The above-mentioned results indicate that this method is accurate, sensitive, and reproducible foridentification and quality assessment of chrysanthemum buds. Furthermore, these methods may be used in further research in other natural agricultural products.

4. Conclusion

In this study, an efficient fingerprinting of chrysanthemum buds was developed by CE coupled with double detection electrodes, which established a quality control protocol based on biochemical makeup for chrysanthemum buds. We hope that this study has provided an appropriate method not only to generate fingerprints of herbs, but also to identify and asses the quality of chrysanthemum buds.

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.

Acknowledgments

This work was supported by the Natural Scientific Foundation of the Higher Education Institutions of Jiangsu Province, China. The authors are grateful for the financial and instrumental support by the Yancheng Institute of Technology.

References

X. Liang, H. Wu, and W. Su, “A rapid UPLC-PAD fingerprint analysis of chrysanthemum morifolium ramat combined with chemometrics methods,” Food Analytical Methods, vol. 7, no. 1, pp. 197–204, 2014.

S. Zhang, S. Dong, L. Chi, P. He, Q. Wang, and Y. Fang, “Simultaneous determination of flavonoids in chrysanthemum by capillary zone electrophoresis with running buffer modifiers,” Talanta, vol. 76, no. 4, pp. 780–784, 2008.

L.-Z. Lin and J. M. Harnly, “Identification of the phenolic components of chrysanthemum flower (Chrysanthemum morifolium Ramat),” Food Chemistry, vol. 120, no. 1, pp. 319–326, 2010.

Pharmacopoeia of People's Republic of China, The State of Pharmacopoeia Commission of People's Republic of China, vol. 1, Chemical Industry Press, Beijing, China, 2010.

K. S. Dattajirao, R. B. Narayana, and B. D. Babasaheb, “Chrysanthemum,” in Postharvest Biotechnology of Flowers and Ornamental Plants, pp. 67–81, Springer, 1990.

Z. Shunying, Y. Yang, Y. Huaidong, Y. Yue, and Z. Guolin, “Chemical composition and antimicrobial activity of the essential oils of Chrysanthemum indicum,” Journal of Ethnopharmacology, vol. 96, no. 1-2, pp. 151–158, 2005.

CDER, Guidance for Industry Botanical Drug Products, U.S. Department of Health and Human Services, Food and Drug Administration Center for Drug Evaluation and Research (CDER), 2004.

Commissioning Process Management Professional (CPMP) and Committee for Medicinal Products for Veterinary Use (CVMP), Note for Guidance on Specifications: Test Procedures and Acceptance Criterion for Herbal Drugs, Herbal Drug Preparations, and Herbal Medicinal and Herbal Medicinal Products, European Medicines Agency (EMEA), 2000.

Drug Administration Bureau of China, Requirements for studying fingerprint of Traditional Chinese Medicine injections (Draft), 2000

Y. Ni, L. Zhang, J. Churchill, and S. Kokot, “Application of high performance liquid chromatography for the profiling of complex chemical mixtures with the aid of chemometrics,” Talanta, vol. 72, no. 4, pp. 1533–1539, 2007.

M. Hajimahmoodi, Y. V. Heyden, N. Sadeghi, B. Jannat, M. R. Oveisi, and S. Shahbazian, “Gas-chromatographic fatty-acid fingerprints and partial least squares modeling as a basis for the simultaneous determination of edible oil mixtures,” Talanta, vol. 66, no. 5, pp. 1108–1116, 2005.

M. Gu, Z. Su, and F. Ouyang, “Fingerprinting of Salvia miltiorrhiza Bunge by thin-layer chromatography scan compared with high speed countercurrent chromatography,” Journal of Liquid Chromatography and Related Technologies, vol. 29, no. 10, pp. 1503–1514, 2006.

X. Liang, H. Wu, and W. Su, “A rapid UPLC-PAD fingerprint analysis of Chrysanthemum morifolium Ramat combined with chemometrics methods,” Food Analytical Methods, vol. 7, no. 1, pp. 197–204, 2014.

M. Gu, S. Zhang, Z. Su, Y. Chen, and F. Ouyang, “Fingerprinting of Salvia miltiorrhiza Bunge by non-aqueous capillary electrophoresis compared with high-speed counter-current chromatography,” Journal of Chromatography A, vol. 1057, no. 1-2, pp. 133–140, 2004.

M. G. Schmid, “Chiral metal-ion complexes for enantioseparation by capillary electrophoresis and capillary electrochromatography: a selective review,” Journal of Chromatography A, vol. 1267, pp. 10–16, 2012.

S. E. Deeb, H. Wätzig, and D. A. El-Hady, “Capillary electrophoresis to investigate biopharmaceuticals and pharmaceutically-relevant binding properties,” TrAC—Trends in Analytical Chemistry, vol. 48, pp. 112–131, 2013.

G. Chen, Y. Zhu, Y. Wang, X. Xu, and T. Lu, “Determination of bioactive constituents in traditional Chinese medicines by CE with electrochemical detection,” Current Medicinal Chemistry, vol. 13, no. 21, pp. 2467–2485, 2006.

J. Ye and R. P. Baldwin, “Amperometric detection in capillary electrophoresis with normal size electrodes,” Analytical Chemistry, vol. 65, no. 23, pp. 3525–3527, 1993.

X. Xing, X. Shi, H. Zhang, W. Wang, and J. Ye, “Determination of diethylene glycol in toothpaste by capillary electrophoresis with electrochemical detection,” Microchimica Acta, vol. 167, no. 3-4, pp. 297–302, 2009.

M. Goodarzi, P. J. Russell, and Y. V. Heyden, “Similarity analyses of chromatographic herbal fingerprints: a review,” Analytica Chimica Acta, vol. 804, pp. 16–28, 2013.

B. J. Yang, J. H. Chen, F. S.-C. Lee, and X. Wang, “GC-MS fingerprints for discrimination of Ligusticum chuanxiong from Angelica,” Journal of Separation Science, vol. 31, no. 18, pp. 3231–3237, 2008.

Y. Jin, T. Liang, Q. Fu et al., “Fingerprint analysis of Ligusticum chuanxiong using hydrophilic interaction chromatography and reversed-phase liquid chromatography,” Journal of Chromatography A, vol. 1216, no. 11, pp. 2136–2141, 2009.

X. Xing and Y. Cao, “Determination of 3-chloro-1,2-propanediol in soy sauces by capillary electrophoresis with electrochemical detection,” Food Control, vol. 18, no. 2, pp. 167–172, 2007.