Chromatography Research InternationalVolume 2012 (2012), Article ID 851792, 12 pagesdoi:10.1155/2012/851792

Research Article

Quality Control Methodology and Their Application in Analysis on HPLC Fingerprint Spectra of Herbal Medicines

Zou Hua-Bin,¹ Du Ai-Qin,¹ Zhang Xin-Ling,¹ Wei Pei-Hai,² Lu Wei-Jie,¹ Yang Guo-Sheng,¹ and Hassan Y. Aboul-Enein³

¹School of Chemistry and Chemical Engineering of Shandong University, Shandong, Jinan 250100, China²Department of Chemistry and Chemical Engineering, Shandong Institute of Education, Shandong, Jinan 250100, China³Medicinal and Pharmaceutical Chemistry Department, National Research Centre, Dokki, Cairo 12311, Egypt

Received 25 June 2011; Revised 25 July 2011; Accepted 25 July 2011

Academic Editor: Teresa Kowalska

Copyright © 2012 Zou Hua-Bin et al. 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.

As traditional Chinese medicine (TCM) is gradually accepted by many countries, people pay much attention to the quality of herbal medicines. Because of the significant variation in active components in them, the quality control of herbal medicines is a very important issue. Nowadays, high-performance liquid chromatography (HPLC) fingerprint spectra (FPS) are widely used in identification and quality control of herbal medicines. This paper will analyze the methodology and their application in identifying and evaluating herbal medicines by means of HPLC FPS, which includes simple comparing, clustering, principal component analysis (PCA), and similarity analysis methods.

1. Introduction

Traditional Chinese medicine (TCM) has been developed and used in China for nearly three thousands of years. Many countries, including Japan, Korea, and countries in south of China have benefited from the TCM for thousands of years. TCM possesses great advantage in curing and preventing diseases.

Compared with man-made synthetic drugs, herbal medicines contain many components which are pharmacologically active. However, herbal medicines also have their shortcoming since the concentration of their active components may vary from batch to batch thus affecting their efficiency in treating diseases. For example, the concentration nd contents of the same kind herbs originated from different regions or from the same region collected at different times may change distinctly.

Even the quality of the same batch herbal medicine stored under different conditions may vary significantly. herbal medicines of the same kind planted or wild usually differ from each other greatly. Therefore, it is essential to ensure the quality of herbal medicines though effective analytical methods.

The quality control involves three steps. The first is false and true identification, the second is to distinguish originating regions of herbs, and the third is quality evaluation [1]. The false and true identification aims to distinguish the species by means of many qualitative analytical methods [1]. The qualities of herbs are closely related to their producing areas; for this reason the determination of producing regions is critical. The quality of herbs depends on the growing environments, collecting times, and storing conditions as well, since the growth of herbs is easily affected by geographical and climate conditions.

The quality control methods underwent many developments since ancient times, from the botany shapes, microscopy structure identification to the physical and chemical properties based on the major components identification to almost all components identification depending on fingerprint spectra (FPS) [2]. The classification of herbs based on fingerprint spectra of herbs is now becoming the platform in identifying herbs. Currently, fingerprint spectra analysis includes two major aspects which are based on spectroscopy fingerprint spectra such as infrared spectroscopy and ultraviolet spectroscopy. And the second is based on the HPLC fingerprint spectra. The spectral fingerprinting techniques are quick, easy, and accurate while the HPLC method is able to determine the partial components in herbs, and can determine their concentrations quantitatively. For this reason, HPLC FPS is currently considered a critical method in evaluating quality of herbal medicine.

In this paper we will summarize systematically the methods and their application in herbal quality control. The common methods used in identifying herbal medicines based on HPLC fingerprint spectra are discussed including the direct comparing method, the analysis on similarity, dual index method, the pattern recognition methods, such as principal component analysis (PCA), clustering, and the invariableness analysis of biological system.

2. Comparing Methods

The directly compared analysis is the classical method in analyzing IR and UV fingerprint spectra. The method depends on the determination and comparison of the HPLC FPS of different herbs and herbal medicines, and the choice of their key properties. The method is easy and reliable.

Hu et al. [3] compared the HPLC FPS of Fu Ling peels originated from different regions. They are the black peels of Poriacocos (Schw.) Wolf. The HPLC FPS of the extracts were measured. The experiments showed that methanol and 95 percent ethanol are the best solvents for extracting components in the peels. The HPLC FPS of the extracts of 10 samples were detected.

There are 17 common peaks in the FPS, with prominent large relative areas and better peak configurations which are present in every FPS. Peak No. 8 was selected as the reference to calculate the relative retention times of other peaks. The relative areas of all common peaks were calculated based on the peaks of extracts from Sichuan province. The 17 common peaks of every extracts are compared directly. The results expressed that the major components of 10 samples are of little differences, but their contents vary greatly. The contents of components in sample from Sichuan province are higher than that of other samples. Among these peaks, the relative areas of peaks no. 3, 4, 6, 7, 8, 14, and 15 in FPS of sample of Sichuan are higher than that of peaks in all other samples’ FPS. The relative peak areas of no. 5, 9, 11, 13 are higher in FPS of sample from Anhui province than that in other samples. The relative areas of peaks no. 1, 16, 17 in FPS of sample from Luo Tian of Hubei province are the highest. Peak no. 10 is the big one in FPS of sample from Hunan province and Ying Shan of Hubei province.

Li et al. [4] reported the HPLC FPS of 10 Fen Ge herbs (the root of Pueraria thomsonii Benth.) from various areas of Guangxi province, S1(from Nanning), S2 (Guilin), S3 (Nanning), S4 (Nanning), S5 (Liuzhou), S6 (Nanning), S7(Guilin), S8 (Nanning), S9 (Nanning), S10 (Guangxi). The HPLC FPS of the 10 samples were extracted with 30 percent of ethanol and were measured. Peak No. 5 was chosen as the reference and to calculate the relative retention times and relative areas of other peaks in the FPS of 10 extracts. In the HPLC FPS, there exist 15 major characteristic common peaks (for every HPLC FPS the sum of the 15 peak areas occupies 90 percent of the total peak area).

The peaks of higher relative area are peaks No. 5, 7, 11, 13 in HPLC FPS of 10 samples. These 15 peaks can represent the common properties of Fen Ge herbs from different regions. On the other hand, the same peaks vary greatly for different samples, and the integrate quality cannot be evaluated in detail by directly comparing these HPLC FPS of Fen Ge herbs.

The HPLC FPS of seeds of Shui Hong Hua (Polygon orienta (L.)) were analyzed by Xie et al. [5]. The HPLC FPS of 9 samples extracts were carried out. Eleven common peaks in the FPS were observed. Peak No. 8 was chosen as a reference peak to calculate the relative retention times and relative areas. There are distinct differences among the relative areas of peaks in FPS of these samples, which explain that the qualities of the 9 samples are significantly different. But using the comparing method is unable to further analyze the quality of these nine samples.

Huang and coworkers [6] studied the quality of Huang Qi (the root of Astragalus membranaceus (Fisch) Bge. Var. mongholicus (Bge). Hsiao) with HPLC FPS. The traditional quality control for Huang Qi only focused on the content of astragalosideⅣ, which is not suitable to reflect the natural quality of the herbs. The HPLC FPS of 5 samples were determined, and it was found that the FPS are similar to each other. There are 13 common peaks in FPS of the 5 samples. The relative retention times and relative peak areas were calculated by reference to the retention time and peak area of astragalosideⅣ. The major peaks in FPS of every sample are very similar. However, their contents are obviously different.

Wang et al. [7] researched the HPLC FPS of Jin Yin Hua, the flower of Lonicera japonica from different regions. The examples were extracted with water, and then ethanol was added into the solutions till to 70 percent. The HPLC FPS of components solved in 70 percent ethanol were measured.

Ten samples are S1, S7 (from Pingyi of Shandong,) S2, S8 (Mixian of Henan), S3, S5 (Hebei), S4 (Xinhua of Hunan), S6 (Benxi of Liaoning), S9, and S10 (Shucheng of Anhui). The relative retention times and relative peak areas were computed by reference to the retention time and peak area of Chlorogenic acid (peak 3). For HPLC FPS of each sample, there are about 15 to 22 peaks. There are 11 characteristic peaks in the FPS of 10 samples. The relative retention times of the 11 peaks are 0.33, 0.64, 1.00, 1.10, 1.21, 1.25, 1.40, 1.74, 2.03, 2.07, and 2.31, respectively. For the samples from the same region, 8 big peaks for each HPLC FPS are different, and their relative peaks areas vary greatly, which show that their qualities differ from each other seriously. However, the comparing method is unable to evaluate their qualities in more detail.

According to the examples described above, one can conclude that the HPLC FPS are capable of providing useful information associated with the herbs’ quality, which can be applied to be a platform for establishing the qualities of herbal medicines. However, the direct comparative method is not suitable for quantitative purposes.

3. Clustering Analysis

Clustering analysis is the catalogue of method that belongs to unsupervised analytical pattern methods, with which samples can be classified objectively and clearly. The methods are wildly applied to analyzing complex systems.

The HPLC FPS of isoflavones were reported by Shi et al. by means of clustering analysis [8]. Isoflavones are the extracts of soybean Glycinemax (L.) Merr. (Phaseolusmax L.), which are used to preventing cancers and diseases of blood vessel related to heart and brain. The components of the 25 samples, namely, S1(Lu Dou 10), S2 (Lu Dou 9), S3 (Qi Mao Dou), S4 (Qi Huang 29), S5 (Huang Ku Dou), S6 (Qin Dou 9), S7 (Nan Zhan 1), S8 (Qi Huang 27), S9 (Qi Huang 31), S10 (Lu 98-8), S11 (Ping Ding Huang), S12 (Yue jin 10), S13 (Tai 75), S14 (Fen 61), S15 (Huai Dou 6), S16 (Tai 292), S17 (Zheng 9528-8), S18 (Shan ning 10), S19 (Lu 6), S20 (93127-4), S21 (Dong jie 10), S22 (Bin Zhi Dou 1), S23 (Qi Huang 1), S24 (Ji Dou 12), and S25 (Zhong Huang 24) were extracted with petroleum ether, and then the residues were extracted with 70 percent of ethanol by means of supersonic waves. The HPLC FPS of the isoflavones of the 25 samples were determined.

In these FPS there are 23 common peaks for these samples. The relative retention times and relative areas of these peaks were calculated by reference to the peak of Genistein, and the matrix with 23 row and 23 columns was constructed. It was analyzed with the method of between-groups linkage and Pearson correlation in SPSS 11.0 version. The results indicate that these 25 samples could be divided into three classes, in which S1, S2 belong to class III, and S4, S7, S14, S18, S19, S21, and S25 are in class II, other samples belong to class I. The FPS of samples in class I are used to establish the common model, and then the FPS of 25 samples were investigated based on this common model. The results indicate that the similarities of samples in class I are larger than 0.93, and that of samples in class II are in the range of 0.91 ~ 0.93, while that of samples in class III are less than 0.91. These results are in agreement with that of clustering analysis.

Dong et al. [9] investigated the HPLC FPS of Chuan Xin Lian herbs from different districts. The chuan Xin lian herbs are the dried upper ground part of Andrographis paniculata (Burm.f.) Nees. The FPS of extracts of 23 samples, no. 1, 3 11 (Bozhou of Anhui), 2 (market), 4, 5 (Yongkang), 6, 7 (Hainan), 8 (Guangdong), 9, 12 (Linquan), 10 (Yulin), 13 (market), 14, 15 (Zhaoqing), 16, 17 (Qingyuan), 18, 19 (Maoming), 20, 21(Yingde), 22, 23 (Zhaodong), were determined. The classical HPLC fingerprint spectra was plotted. Twenty three major peaks were chosen in the FPS, which were able to reflect the properties of samples. A matrix with 23 rows × 23 columns was built up, which was classified depending on Euclidean distance.

These 23 samples can be classified into three groups; the samples from Bozhou city of Anhui province and Linquan are in one group. Samples obtained from Hainan and Guangxi provinces are in the second group. Samples from Zhaodong of Hunan province and from districts of Guangdong province are the third group. The results indicate that Chuan Xin Lian samples originated from the close areas are similar to each other. Furthermore, the matrix was dissolved resting on nonlinear map method; the results agree with that by cluster analysis.

Li et al. estimated the qualities of Xiang Jia peels from different regions with HPLC FPS [10]. Xiang Jia peel is the dried bark of Periploca sepium Bunge. The HPLC FPS of components of the 15 samples, No. 1 (Shandong), 2 (Jiaozuo of Henan), 3 (Dandong of Liaoning), 4 (Weinan of Shanxi), 5 (Zhejiang), 6 (Baoding of Hebei), 7 (Nanyang of Henan), 8 (Gansu), 9 (Yuci of Shanxi), 10 (Yuncheng of Shanxi), 11 (Heilongjiang), 12 (Anguo of Hebei), 13 (Xinyang of Henan), 14 (inner Mongolia), 15 (Shenyang of Liaoning), extracted with 70 percent of methanol were plotted. There were 19 characteristic peaks in these HPLC FPS, and they were clustered by means of SPSS software, in which the peak areas of unit mass of herbs were selected as variableness, and a matrix with 15 rows ⅹ19 columns was established. It was analyzed with the within-groups linkage method depending on the Euclidean distance. The results showed that the 15 samples are divided into 4 classes. Samples no. 1, 3, 4, 6, 10 are in one class, samples no. 7, 8 are in a second class, samples no. 14, 15 belong to a third class, while samples no. 2, 5, 9, 11, 12, 13 are grouped in a fourth class. A common model was set up ground on the FPS of samples no. 2, 5, 9, 11, 12, and 13, with which the similarities of the 15 samples were established. In conclusion, the similarities of samples no. 1, 3, 4, 6, and 10 in the first class are in the range of 0.80–0.88, below 0.90, ranked among the qualified products. The similarities of samples in the other three classes are larger than 0.90, ranked among excellent products, which fit to the results gained by cluster analysis and are in line with that identified by experts.

The analytical method about the HPLC FPS of Ku Shen samples was established by Zhang et al. [11]. Ku Shen is the dried root of Sophora flavescens Ait. The quality of Ku Shen is usually controlled by detecting the contents of matrine and alkaloids which are unable to represent the quality relative to all components in Ku Shen accurately. The authors established the HPLC FPS of flavonoids and alkaloids, which were employed to evaluate the quality of 24 Ku Shen samples, No. 1 (Zuoquan), 2 (Anze), 3 (Licheng), 4 (Yuncheng), 5 (Taiyuan), 6 (Changzhi) were collected from Shanxi province, 7 (Chengxian), 8 (Qingshuixian) were from Gansu, 9 (Niute Qi), 10 (Yuanbaoshan) were from inner Mongolia, 11 (Anguo), 12 (Xingtai) and 13 were from Hebei, 14 (Hanyang), 15 (Xianyang) and 16 were from Shanxi, 17 (Liaoning), 18 (Zhengzhou) and 19 (Wenxi) from Henan, 20 (Weishan of Yunnan), 21 (Changsha of Hunan), 22 (Anhui), 23 (Yinchuan of Ningxia), 24 (Maguan of Yunnan). The FPS of flavonoid components (A) extracted with 50 percent of methanol and alkaloid components (B) extracted with 2 percent of H₃PO₄ solution were carried out. There are 30 characteristic peaks in the FPS of (A) and 16 characteristic peaks in the FPS of (B).

The extracts pattern was recognized depending on the 46 peaks by means of the within-groups linkage relying on the Euclidean distances of the relative peak areas of the 46 peaks. The results indicate that the 24 samples can be separated into 3 classes combining the results based on shape identification. Class I includes samples no. 1, 2, 3, 4, 6, 8, 11, 12, 13, 19, 21, and 23. While class II includes samples no. 5, 7, 9, 10, 14, 15, 16, 17, 18, 20, 22. The class III has only one sample No. 24. Among class I and II are true genuine Ku Shen herbs, while class III represents the false product. The similarities of 24 samples were analyzed reckoning on the common model; the results reveal that the similarities of samples in class I are larger than 0.90, in class II range from 0.80 to 0.88, and that in class III, the false product of ku Shen is less than 0.80.

Xu et al. studied the HPLC FPS of Dan Shen [12], the dried root and stem of Salvia milionhiza Bage. The quality of Dan Shen herbs varies with the different regions significantly. In this report 99 Dan Shen samples were collected from10 different districts. The HPLC FPS of components of these samples extracted with methanol were determined. The principal component analysis on the relative areas of 5 common peaks were studied for 47 cultured Dan Shen samples, Bzh-J-1-4 from Bozhou (Anhui), Ang-J-1-8 from Anguo (Hebei), Jin-J-1-11 from Jinan (Shandong). Lsh-J-1-7 from Lushi (Henan). Ysh-J-1-21 from Yishui (Shandong). Bsh-J-1~7 from Boshan (Shandong); Wild Dan Pi: anq-Y-1-9 from Anqiu (Shandong). Lsh-Y-1~8 from Lushi (henan). Ysh-Y-1~21 from Yishui (Shandong). Bsh-Y-1~14 from Boshan (Shandong).

Their retention times were at 9.45, 11.35, 14.84, 17.87, and 22.25 min. and were performed with SPSS 11.0 version. The similarities of these 47 samples were enumerated with Cosine method in terms of the 5 common peaks, and the within-group average distances between every individual sample and subclasses were also calculated.

The samples from Anguo of Hebei province, Boshan of Shandong province, and Bozhou of Anhui province can be classified in terms of their original regions. The samples from Jinan of Shandong province, Lushi of Henan province cross with each other. The samples from Yishui of Shandong province are obviously different. The 52 wild Dan Shen samples were clustered based on the 5 common peaks. The distances between every individual sample were computed with the Cosine method, and the within-group linkage distances between every individual and subclasses, and between subclasses were also obtained. The results indicate that there are great differences between the same common peaks of different samples with regards their peak areas for wild samples obtained from the same regions.

The HPLC FPS of Dan Pi herbs from different regions were investigated by Wu et al. [13]. Dan Pi is the dried peel of Paeonia suffruticosa Andr. roots. The contents of components in Dan Pi herbs may change obviously with the originated regions, growing conditions, and processing methods of herbs. The HPLC FPS of components of 13 Dan Pi samples extracted with methanol were recorded. There are 13 common peaks existed in these FPS. The correlation coefficient between these samples was calculated, and the were as the distances between samples. The samples were classified based on the distances.

The results showed that the 13 samples were divided into 2 classes. The first includes samples no. 1, 2, 3, 4, 9, 11, 5, 10, 13, 6, 12, which can be reclassified into two subclasses. Subclass I has samples no. 13, 6, 12 while subclass II includes samples no. 1, 2, 3, 4, 9, 11, 5, and 10. The second class involves samples no. 7, 8. It was found that subclass II in the first class (samples no. 1, 2, 3, 4, 9, 11, 5, and 10) comes from Bozhou of Anhui province. Although the processing methods are different, their HPLC FPS are highly similar, while samples no. 7, 8, 13, 6 and 12 are distinctly different from the samples obtained from Bozhou distinctly. These results demonstrate that the processing methods affect the qualities of Dan Pi to some extent. The originated regions are their major impact factor on their qualities.

Yu et al. [14] investigated the HPLC fingerprint of fruiting bodies of cultured Cordyceps militaris. The Cordyceps species of the traditional Chinese medicinal mushrooms are entomopathogenic fungi. Cordyceps militaris, also known as the Chinese caterpillar fungus, possesses pharmacological activities, and according to some studies more potential than that of C. sinensis (also known as Dong Chong Xia Cao) that is used in certain health food products in Asia. Eleven fruiting bodies of C. militaris cultured by different companies from six provinces of China were examined. The HPLC FPS of components of 11 samples, no. 1 (Shenyang of Liaoning 1), 2 (Shenyang of Liaoning 2), 3 (Beijing 1), 4 (Beijing 2), 5 (Hohhot of Inner Mongolia), 6 (Heze of Shandong), 7 (Dongtai of Jiangsu 1), 8 (Dongtai of Jiangsu 2), 9 (Jiangmen of Guangdong), 10 (Xinhui of Guangdong 1), 11 (Xinhui of Guangdong 2), extracted with water by supersonic technique and the HPLC fingerprint chromatograms were recorded. The clustering analysis was operated in SPSS software.

Using this method, the 11 samples can be classified into two broad categories containing 6 and 5 samples, respectively.

The average of peaks areas for samples no. 1, 2, 3, 5, 6, and 9 was selected to be the common model, and the similarities of all the fruiting bodies were analyzed based on this model. The results illustrated that the correlative coefficient is larger than 0.887 and the Cosine value of vectorial angle is larger than 0.943, which display that these 11 samples are of similar quality. Based on the retention time, 11 common peaks were determined. Peaks 7, 9, and 11 were identified as uridine, adenosine, and cordycepin, respectively. Using the reference fingerprint, fruiting bodies of cultured C. militaris could be easily identified and assessed.

4. Principal Component Analysis (PCA)

Chen et al. [15] studied the false and true of Ren Shen (Radix Ginseng) by means of PCA and Fisher factor methods. This paper calculated the Fisher factors, based on the principle that the distances between classes are extremely large and that between samples in a class is of the minimum values for identifying herbal medicines. Twenty-four samples relative to Ren shen are obtained from originated regions in Benxi of Liaoning province and the Chang bai mountain of Jilin province. They were major roots of red Ren Shen (Samples no. 1 ~ 12), Shen Lu (Samples no. 13 ~ 16), Shen Xu (Samples no. 17 ~ 20), and raw Ren Shen (Samples no. 21 ~ 24). The HPLC FPS of components extracted with 70 percent of ethanol were measured. These FPS were analyzed in terms of the Fisher factor and PCA method. The outcomes reveal that the Fisher factor method with two main factors FF1 and FF2 is better than PCA with two main factors PC1 and PC2 in identifying these samples. The results indicate that the main roots of red Ren Shen, Shen Xu, Shen Lu, and the dried root of raw Ren Shen can be determined clearly in FF1 ~ FF2 figure, but it is impossible for these samples to be divided into different groups efficiently in PC1 ~ PC2 figure.

The Chuan Xiong herbs were identified with PCA, cluster, and Fisher factor methods by Chen et al. [16]. Chuan Xiong herb is the root of Ligusticum chuanxiong Hort. The HPLC FPS of components extracted with water of 21 samples from different regions were determined, samples no. 1 ~ 4 from Yuxi of Yunnan province, samples no. 5 ~ 8 collected from Guanxian of Sichuan province, samples no. 9 ~ 12 from Xianning of Hubei province, samples no. 13~16 from Jiujiang of Jiangxi province, samples no. 17 ~ 20 brought from markets, and sample no. 21 the false product from market. Among these FPS, there are 15 common peaks, and their relative peak areas for every peak were computed by means of normalized method of peak area. The patterns of these samples were recognized with PCA, cluster and Fisher factor methods. Based on the results, the samples no. 1 ~ 4 from Yuxi, no. 5 ~ 8 from Guanxian, no. 9 ~ 16 from Jiujiang form three groups, separately. There are 15 peaks in these FPS, which can reflect the properties of Chuan xiong herbs from different original regions accurately. The points of the samples no. 9 ~ 12 are diverged significantly, which show the obvious varieties among these 4 samples. Samples no. 17 ~ 20 are close to samples from Hubei and Jiangxi provinces. It exhibited similar qualities to each other. The clustering results match with that achieved by means of PCA. The Fisher factor method is able to distinguish samples from Xianning and Jiujiang further. The samples from markets are analogous to that from Xianning, which imply that these samples may be originated from Xianning.

Zhi Shi is the dried immature fruit of Suan Cheng (Citrus aurantium L.) and Tian Cheng (Citrus sinensis (L.) Osbeck). Zhao et al. [17] took the chemical pattern recognition to classify Zhi Shi herbs. The HPLC FPS of components of 15 samples, no. 1 ~ 3, 10 originated from Sichuan. 4–7, 9 from Jiangxi, 8, 11, 12, 14, 15 from markets, 13 from Guangxi, were extracted with methanol detected and analyzed based on PCA. The outcomes were compared with that by K-mean clustering analysis. The self-scaled data of peak areas were pattern recognized with K-mean clustering method. The results showed that samples no. 1, 2, 3, 8, 10, 11, 13, 14, 15 belong to a class, and samples no. 4, 5, 6, 7, 9, 12 are classed in another class. The self-scaled data were dealt with PCA, and the results are the same as that obtained by K-mean method. Samples no. 8, 11, 14, 15 obtained from markets are similar to that from Sichuan and Guangxi greatly, which means samples no. 8, 11, 14, 15 may be cultivated in the two previously mentioned provinces.

Yang et al. [19] evaluated 29 extracts of Yin Xing (Ginkgo biloba) with principal sensitivity vector regression (RPPSV) method based on the HPLC FPS. The FPS of components of the Yin Xing extracted with methanol were determined. The results indicate that 7 samples no. 15, 16, 17, 18, 19, 25, and 29 are abnormal ones. Based on the PC1 ~ PC2 ~ PC3 figure, one can find that the 7 abnormal samples are far away from the 22 normal samples. The results confirm that RPPSV combined with MCCV is able to distinguish the qualified samples from abnormal ones. Yi et al. [20] investigated the HPLC FPS of Chen Pi (Pericarpium citri reticulatae Blanco) of 22 samples, no. 1, 4 Pericarpium Citri Reticulatae (originated from Guangdong), 2, 3, 5, 6, 13, 14 Pericarpium Citri Reticulatae (from markets), 7, 8, 9 Pericarpium Citri Reticulatae (from Hubei, Hunan and Guangxi), 10, 17 Pericarpium Citri Reticulatae (Citrus reticulata “Dahongpao”) (from Sichuan and Zigong of Sichuan), 11, 12 Pericarpium Citri Reticulatae (from Shanghai), 15 Pericarpium Citri Reticulatae (from Zhejiang), 16 Pericarpium Citri Reticulatae (Citrus reticulate cv. chachiensis) (from Xinhui of GUangdong), 18 peel of tangerine(from Wenzhou), 19 peel of Citrus sinensis Osbeck (from Guangdong), 20 peel of “Shatang” tangerine (from Guangdong), 21 peel of sweet tangerine (from Guangdong), 22 peel of Citrus grandis (L.) Osbeck. The matrix of measured data of HPLC FPS was evaluated. The results gained by PCA method are as follows: the first PC₁ characteristic value is ; its contribution ratio is 74.24%. The second PC₂ characteristic value is ; its contribution ratio is 8.70%. The third PC₃ characteristic value is ; its contribution ratio is 6.30%. The sum of contribution ratios of the combined PC is 89.24%.

Relying on the graph based on the three score vectors, sample 22 differs from other 21 samples extremely. The other 21 samples were analyzed by PCA; the sample 18, 19, and 20 are different from the other 19 samples, which are not suitable for herbal medicines. The samples apart from sample 18, 19, 20, and 22 can be divided into two classes. Samples 1, 4, 9, 10, 16, and 17 belong to the first class, and samples 2, 3, 5, 6, 7, 8, 11, 12, 13, 14, 15, and 21 are in the second class. The samples in the first class were all from Guangdong, Guangxi and Sichuan provinces, and that in the second class all produced in Hubei, Hunan, Jiejiang provinces, and Shanghai.

The HPLC FPS of commercial samples of Ginkgo biloba extracts (EGb) obtained from different sources were studied by Xie et al. [18]. The HPLC FPS of components of the 19 samples extracted with methanol were carried out and shown in Figure 1.

Figure 1: The HPLC fingerprints of 19 commercial samples of Ginkgo biloba extracts (EGb) from different sources (see [18]).

To observe and compare the chromatograms of the sample solutions, respectively, against the reference fingerprint of EGb761 (EGb761; Schwabe, Germany) using the HPLC fingerprint of EGb761 as the standard pattern against which to compare other preparations, 19 samples of EGb from different sources were comparatively analyzed. Calculating the raw signal points set of all samples by using the CASE software, the results showed a high degree of similarity of the samples collected to the EGb761 represented by a correlation coefficient of more than 0.94; five batches showed a lower degree of similarity represented by a correlation coefficient of less than 0.87. This indicates that the proportion and distribution of the total flavonoids in most extracts of Ginkgo biloba leaves possess a high level of consistency. Additionally, the fingerprint analysis shows that three of the products (samples no. 1, 2, and 4) were adulterated, likely with the inexpensive flavonoid rutin, which can be used to artificially increase the total flavonoid content. This was further confirmed by principal component analysis (PCA) (Figure 2). The projection points of the samples no. 1, 2, and 4 are far away from the main body in the graph although the producers declared the quality of their products to be in accordance with the standardized EGb specification. Had the three adulterated ginkgo extracts only been analyzed by quantitation of total flavonoids by conventional HPLC test, rather than by pattern recognition, this adulteration would not be evident.

Figure 2: The score plot obtained by principal components analysis (PCA) of 19 samples of EGb (see [18]).

Yi et al. [21] researched the HPLC FPS of Pericarpium Citri Reticulatae and Pericarpium Citri Reticulatae Viride. Pericarpium Citri Reticulatae (PCR) is the dried peel of mature tangerine and its mutations, collected from September to December. Pericarpium Citri Reticulatae Viride (PCRV) is the dried peel or dried immature fruit of immature tangerine and its mutations, collected from May to August. The summary of 60 samples is given in Table 1.

Table 1: Summary of the tested samples (from see [21]).

No.
Sample name
Source
Year of collection
No.
Sample name
Source
Year of collection

1
PCR-A
Xinhui, Guangdong
2002
31
PCR-C
Purchased from Jiejiang
Unknown

2
PCR-A
Xinhui, Guangdong
2003
32
PCR-C
Purchased from Hunan
Unknown

3
PCR-A
Xinhui, Guangdong
2003
33
PCR-C
Purchased from Henan
Unknown

4
PCR-A
Xinhui, Guangdong
2003
34
PCR-C
Purchased from Henan
Unknown

5
PCR-A
Xinhui, Guangdong
2003
35
PCR-C
Purchased from Guangdong
Unknown

6
PCR-A
Xinhui, Guangdong
2003
36
PCRV-A
Xinhui, Guangdong
2004

7
PCR-A
Xinhui, Guangdong
2003
37
PCRV-A
Xinhui, Guangdong
2004

8
PCR-A
Xinhui, Guangdong
2003
38
PCRV-A
Zigong, Sichuan
2004

9
PCR-A
Xinhui, Guangdong
2003
39
PCRV-A
Zigong, Sichuan
2004

10
PCR-A
Xinhui, Guangdong
2003
40
PCRV-A
Zigong, Sichuan
2004

11
PCR-A
Xinhui, Guangdong
2004
41
PCRV-A
Zigong, Sichuan
2004

12
PCR-A
Xinhui, Guangdong
2004
42
PCRV-A
Zigong, Sichuan
2004

13
PCR-A
Xinhui, Guangdong
2004
43
PCRV-A
Zigong, Sichuan
2004

14
PCR-A
Xinhui, Guangdong
2004
44
PCRV-A
Zigong, Sichuan
2004

15
PCR-A
Zigong, Sichuan
2004
45
PCRV-A
Zigong, Sichuan
2004

16
PCR-A
Zigong, Sichuan
1995
46
PCRV-A
Zigong, Sichuan
2004

17
PCR-A
Zigong, Sichuan
1997
47
PCRV-A
Zigong, Sichuan
2004

18
PCR-A
Zigong, Sichuan
2000
48
PCRV-A
Zigong, Sichuan
2003

19
PCR-A
Zigong, Sichuan
2004
49
PCRV-A
Changsha, Hunan
2004

20
PCR-A
Zigong, Sichuan
2004
50
PCRV-A
Changsha, Hunan
2004

21
PCR-A
Zigong, Sichuan
2004
51
PCRV-A
Changsha, Hunan
2004

22
PCR-A
Changsha, Hunan
2004
52
PCRV-A
Changsha, Hunan
2004

23
PCR-C
Purchased from Anhui
Unknown
53
PCRV-C
Purchased from Henan
Unknown

24
PCR-C
Purchased from Guangxi
Unknown
54
PCRV-C
Purchased from Guangdong
Unknown

25
PCR-C
Purchased from Heilongjiang
Unknown
55
PCRV-C
Purchased from Fujian
Unknown

26
PCR-C
Purchased from Hebei
Unknown
56
PCRV-C
Purchased from Guangxi
Unknown

27
PCR-C
Purchased from Henan
Unknown
57
PCRV-C
Purchased from Henan
Unknown

28
PCR-C
Purchased from Hubei
Unknown
58
PCRV-C
Purchased from Anhui
Unknown

29
PCR-C
Purchased from Shanghai
Unknown
59
PCRV-C
Purchased from Guangdong
Unknown

30
PCR-C
Purchased from Shanghai
Unknown
60
PCRV-C
Purchased from Heilongjiang
Unknown

PCR-A and PCRV-A: authentic Pericarpium Citri Reticulatae (PCR) and Pericarpium Citri Reticulatae Viride (PCRV) samples collected from original producing areas (PCR-A and PCRV-A from Xinhui (Citrus reticulata “Chachi”), PCR-A and PCRV-A from Zigong (Citrus reticulata ‘Dahongpao’), PCR-A and PCRV-A from Changsha (Citrus erythrosa Tanaka); PCR-C and PCRV-C: commercial Pericarpium Citri Reticulatae and Pericarpium Citri Reticulatae Viride samples purchased from 11 difference provinces and cities (from [21]).

Table 2: Crude drug samples of Radix polygoni multiflori (from [22]).

Sample
Source
Year of collection
Sample
Source
Year of collection

1
Zhangshu, Jiangxi
2002.01
19
Deqing I, Guangdong
2003.12

2
Beijing
2002.02
20
Deqing II, Guangdong
2003.12

3
Bozhou, Anhui
2002.02
21
Deqing III, Guangdong
2003.12

4
Shanghai
2002.02
22
Deqing IV, Guangdong
2003.12

5
Zhengzhou, Henan
2002.04
23
Deqing V, Guangdong
2003.12

6
Hankou, Hubei
2002.06
24
Deqing VI, Guangdong
2003.12

7
Chengdu I, Sichuan
2002.06
25
Deqing VII, Guangdong
2003.12

8
Chengdu II, Sichuan
2002.06
26
Nandan, Guangxi
2003.12

9
Xian, Shanxi
2002.06
27
Duyun I, Guizhou
2003.12

10
Guiyang I, Guizhou
2002.06
28
Duyun II, Guizhou
2003.12

11
Guiyang II, Guizhou
2003.12
29
Simao, Yunnan
2003.12

12
Yuzhou, Henan
2003.11
30
Yuanyang I, Yunnan
2004.01

13
Nanjing I, Jiangsu
2003.11
31
Yuanyang II, Yunnan
2004.01

14
Nanjing II, Jiangsu
2003.11
32
Pingbian, Yunnan
2004.08

15
Qingyang, Anhui
2003.11
33
Xinxian, Yunnan
2004.08

16
Songxian I, Henan
2003.11
34
Mengzi, Yunnan
2004.08

17
Songxian II, Henan
2003.11
35
Enshi, Hubei
2004.03

18
Lushi, Henan
2003.11
36
Yubing, Sichuan
2004.04

The HPLC FPS of components of these samples extracted with methanol and ultrasonator were operated. In this work, the scores plot of PC1 versus PC2 was examined for separation or clusters relating to different groups of PCR and PCRV samples, especially the “mixed peels” samples and authentic samples.

To overview the distribution of these 60 samples, principal component analysis was utilized to classify those HPLC-DAD data. The 2D-projection plot of PCA on the 60 entire chromatograms was performed, and the scores plot demonstrates an interesting result for identification of the authentic products. There are four confined clusters in the 2D projection plot, called PCR-1, PCR-2, PCRV-1, and PCRV-2, which are shown with four different signs. From the plot, it could be easily seen that most of these commercial samples are separated with the authentic ones with only four exceptions. This tells us that only four commercial samples belong to authentic ones. They are samples no.23, 24, 53, and 54. In this work, PCR-1 and PCRV-1, named group “1”, denoted the 39 authentic PCR and PCRV samples and the 4 authentic commercial samples while PCR-2 and PCRV-2, named group “2”, were the other 17 commercial samples bought from markets with unclear plant sources. In fact, there are many tangerine peels in the herbal market from new tangerine mutations, such as Citrus unshiu Marc., Citrus poonensis Tanaka, and so forth, which are called “mixed peels”, and their qualities are uncertain according to traditional experience. The shapes of these two groups of samples are quite similar and even the same. In this work, PCA projection plot was successfully applied to discriminate authentic PCR and PCRV from “mixed peels” PCR and PCRV. In addition, PCR-2 and PCRV-2 could be well separated while PCR-1 and PCRV-1 were crossed and eight samples were wrongly classified.

There are 18 common peaks in these HPLC FPS. In order to evaluate the discrimination ability of these common components, PCA analysis was employed, using their absolute peak areas as input data. The PCA scores plot demonstrated that information obtained from the 18 common components was enough for discrimination of the authentic PCR and PCRV samples from the “mix peels”. Furthermore, it was even better than the result of PCA on the entire chromatograms for distinguishing of PCR-1 and PCRV-1. Five samples were wrongly classified here.

5. Similarity Analysis

Hu et al. [23] researched the HPLC FPS of Huang Qi herb, which is the dried root of Astragalus membranaceus (Fisch) Bge. Var. mongholicus (Bge.) Hsiao and Astragalus membranaceus (Fisch) Bge. The HPLC FPS of components of 12 samples extracted with n-butyl alcohol were determined.

There are 26 common peaks in these FPS, which are analyzed with the Cosine method relying on their peak areas. The results indicate that the similarities among these 12 samples are all larger than 90 percent, which prove that the Huang Qi herbs from Gansu province are similar to each other excellently. Moreover, the contents of astragaloside IV, formononetin, and calycosin were detected. For these 12 samples,the content of astragaloside IV is in the range from 0.7 ~ 13.0 μg/g (herb), that of formononetin is in the range from 0.4 ~ 10 μg/g (herb), and that of astragaloside IV is in the range from 0.4 ~ 2.0 μg/g (herb), which shows obvious varieties.

The HPLC FPS of 14 Zhong jie Feng (Sarcandra glabra Thunb.) samples from 14 different districts were investigated by Wu et al. [24]. The HPLC FPS of components of these samples extracted with water were graphed. These FPS are of 7 common peaks. The similarities were determined with the Cosine method in terms of the relative areas of these 7 peaks. The result showed that the similarities of the samples generated from various districts, collected at different seasons, cultured or wild are all in the range of 0.75 ~ 1.0. The similarities between samples from Guangdong and Jiangxi are larger than 0.83, and that between samples collected in spring and autumn are 0.72, which verify that there are distinct varieties even for the samples originated from the same region, but harvested in different times. The similarities between samples planted and wild are 0.88. The results noted above reveal that depending on the FPS, Zhong Jie Feng herbs from different areas, collected in different times, cultured or wild can be distinguished successfully.

Song et al. [25] studied the HPLC FPS of components of Dan Shen extracted with water. The sample Dan Shen is the root and stem of Salvia miltiorrhiza Bunge. Ten samples were collected from different regions. The FPS of the components were recorded. In these FPS, Peaks, whose relative peak area is larger than 0.6 percent, and its separation degree which is larger than 0.8, are picked as the common peaks. There were 15 common peaks, whose relative retention times and peak areas were compared with that of Danshensuan II peak 12. The similarities of samples referenced to sample 10 were calculated based on the Cosine method. The similarities of S. przewalskii var. mandarinorum compared with the standard sample 10 are only 0.282, which show extreme differences, and similarities of other samples relative to sample 10 are all larger than 0.90. These results elucidate that Dan Shen herbs from different regions are usually of high quality.

Jiang et al. investigated HPLC FPS of 10 Zi Cao herb samples from different districts [26]. The Xinjiang Zi Cao is the dried root of Ameba euchroma (Royle) Johnst. The FPS of components extracted with methanol were obtained and underwent similarity analysis—the overlapping ratio analysis. Based on the results, the overlapping ratios of 6 Xinjiang Zi Cao samples are higher than 66.67 percent relative to the standard Zi Cao sample (sample 10). The 8 peaks with large relative areas for every sample were picked as the characteristic peaks. There are 7 common peaks which exist in every sample of Xinjiang Zi Cao. The retention times relative to each sample’s peak no. 8 are 0.09, 1.00, 1.21, 1.48, 1.65, 1.91 and 1.95, respectively. The contents of shikonin in every sample were measured. Results indicate that there exist no divergences about the contents among samples 2, 3, 4, 6, and the standard sample 10. But samples No. 7, 9 differ from the former greatly in the content. The Xijiang Zi Cao from Afghanistan is different from that from Xinjiang distinctly.

The overlapping ratios of three Ying Zi Cao (Lithospermum erythrorhizon sieb. et Zucc) relative to the sample 10 are 74.07 percent, 53.85 percent, 61.54 percent, respectively. The ratios of peaks existing in the three samples related to the 7 common peaks of Xinjiang Zi Cao all are less than 80 percent. These showed that Zi Cao from different regions of Xinjiang are similar to each other, and Xinjiang Zi Cao from Afghanistan and the three Ying Zi Cao differ from Xinjiang Zi Cao significantly in quality.

Chai and his coworkers investigated the HPLC FPS of Zhi Mu herbs [27], which are the dried roots of Anemarrhena asphodeloides Bge. 8 samples from different regions were S1, S2 (from Bozhou of Anhui province), S3 (Shaoyang of Hunan province), S4 (Nanjing of Jiangsu province), S5 (Jinan of Shandong province), S6 (Yantai of Shandong province), S7 (Taiyuan of Shanxi province), and S8 (Changsha of Hunan province). The FPS of components of these samples extracted with 80 percent methanol were examined.

In these FPS, there are 6 common peaks as the common model, on which the similarities of samples were analyzed related to the common model. The similarities of samples from different districts are all larger than 0.93. The order of similarities arranged from high to low is S1, S2 (>0.996) toS4 (0.976), S7 (0.968), S6 (0.958), S3 (0.947), S8 (0.934), and S5 (0.934). They are all fine qualified herb medicines.

Using HPLC FPS, Fu et al. [28] evaluated the qualities of 7 Chen Pi herb samples, which are the peels of dried mature fruit of Citrus reticulate Blanco. The FPS of components of Chen Pi extracted with water were determined. The qualities of these samples S1, S2 (collected from Hunan province), S3, S4 (from Hubei province), S5, S6, S7 (from Zhejiang province) were evaluated ground on the FPS. There are 7 common peaks existed in these FPS, which were used for similarity analysis by means of the Cosine method in terms of the relative peak areas. The outcomes manifested that that the correlation coefficients are all in the range of 0.9887 ~ 0.9990, which express that these samples are of higher similarity and good quality.

Wu et al. studied the similarities of 36 He Shou Wu herb samples based on their HPLC FPS [22]. He Shou Wu herb is the dried root of Polygonum multiflorum Thunb.

The FPS of the components of 36 samples extracted with 50 percent of methanol were recorded. The common model of these samples was obtained resting on median method; then the similarities were calculated referenced to the common model. According to the results 36 samples can be divided into two classes. The similarities of the first class were in the range of 0.8597 ~ 0.9982 including 30 samples no. 3 ~ 5, 7 ~ 25, 27 ~ 29, and 32 ~ 36. For the second class the similarities of 6 samples no. 1, 2, 6, 26, 30, 31 were ranged from 0.3287 to 0.4715. It verifies that He Shou Wu herbs from different regions can be recognized accurately by similarities analysis.

Yu et al. evaluated the qualities of 11 Bai Zhu herb samples from the same district [29]. Bai Zhu herb is the root of Atractylodes macrocephala Koidz. The HPLC FPS of 11 batches of Bai Zhu, cultured in Youyang of Chongqing city of China, were carried out. The FPS of components extracted with petroleum ether were performed. The relative retention times of peaks were counted related to the peak retention time at  min in each FPS. There are 11 common peaks existed in these FPS, and then the similarities of samples were calculated with correlation coefficient and Cosine methods. The results illustrate that the similarities of all samples are above 0.941 (by correlation coefficient) and 0.938 (by Cosine method), which indicate that these cultured Bai Zhu from the same district are of good quality.

The similarities of Chuan Dan Pi herb samples were analyzed, and their quality evaluation was performed by Yu et al. [30]. The Dan Pi herb is the dried root bark of Paeonia suffruticosa Andr. The HPLC FPS of components of 11 planted Chuan Dan Pi herb samples extracted with methanol were examined, which were collected from Zhijiang district of Chongqing of China city. There are 11 common peaks in these FPS; both their relative retention times and relative peak areas were calculated contrasted to the retention time and peak area of Paeonol peak (the model was established by means of averages of relative retention times and relative peak areas of each corresponding peak in these FPS). The similarities of samples were computed relying on the sample 2 with correlation coefficient and Cosine methods. The similarities are all larger than 0.97, which manifests that these Chuan Dan Pi cultured in the same region are similar to each other extremely.

Wang et al. [31] studied the qualities of Xue Lian collected from Xinjiang of China. Xue Lian herb is the part of Saussurea involucrate Kar. et Kir above ground. The HPLC FPS of components of 10 samples extracted with 70 percent ethanol were determined. The samples were brought from Chinese herbal company of Wulumuqi of Xinjiang. There are 12 peaks in the FPS chosen as common peaks whose relative retention times and relative peak areas are steady. The similarities are in the range of 0.92 ~ 1, which illustrate that these 10 samples are of good quality. In these FPS 7 common peaks were determined by means of HPLC-MS/MS method. The peaks 1, 3, 4, 5, 6, 10, and 11 are Scopolin, Rutin, Isoquercitrin, Lonicerin, Quercetrin, Hispidulin, and Jaceosidin, respectively.

Fan et al. [32] analyzed 10 Gan Cao herb samples with HPLC FPS. Gan Cao herb is the dried root of Glycyrrhiza uralensis Fisch, Glycyrrhiza inflate Bat., or Glycyrrhiza glabra L. In this paper 10 Gan Cao samples come from Hangjin Qi of inner Monggolian, being Glycyrrhiza uralensis Fisch. The HPLC FPS of components extracted with 50 percent of methanol were measured. There are 10 common peaks in these FPS, which occupy more than 90 percent of total peak area. It reflects that these common peaks are able to reflect the quality of these samples. The similarities among these samples were carried out, in which sample 1 was the reference. The similarities of these 10 samples are larger than 0.90. It indicates that these Gan cao samples are excellent in quality.

The qualities of 13 Tu Fu Ling herb samples from different regions were performed by Li et al. [33] with HPLC FPS. Tu Fu Ling herb is the dried root of Smilacis rhizome. The HPLC FPS of components of these 13 samples extracted with 70 percent of ethanol were determined. True and false herb samples are of obvious differences. There are 10 common peaks in the FPS of 10 true samples. The relative retention times and relative areas of peaks in each FPS were calculated in contrast to peak 4 astilbin in every FPS. A common model based on FPS of the true l0 samples was established. The similarities of every sample were determined relying on the common model. Results elucidate that similarities of the 10 samples are higher than 0.93.

Tian et al. [34] investigated the HPLC FPS of Fu Zi herb. Fu Zi herb is the dried root of Aconitum carmichaelii Debx. In this paper, cultured and wild roots of Aconitum carmichaelii Debx were treated with 10 percent of ammonia water and then extracted with ethyl ether. The HPLC FPS of these components were examined. There are around 18 peaks in FPS of every sample, and there are 9 common peaks in these FPS. The sum of peak area of the 9 common peaks occupies 57.3 to 88.6 percent of total peak area for each sample, which show the importance of components corresponding to common peaks in these herbs. The similarities of 14 samples, relative to sample 15 the standard sample, were calculated with correlation coefficient and Cosine methods. The results revealed that similarities of samples 1 (collected from Liupan shui of Guizhou province), 2 (Huize of Yunnan), 3 (Xuanwei of Yunan), 4 (Huize of Yunnan), 6 (Zhaotong of Yunnan), 12 (Lijiang of Yunan), and 13 (Jiangyou of Sichuan) are larger than 0.90. the similarities of sample 11 (Xuanwei of Yunnan), 14 (Jiangyou of Sichuan) are in the range of 0.88 ~ 0.90, and the similarities of samples 5 (Lijiang of Yunnan), 7 (Lijiang of Yunan), 8 (Zhaotong of Yunnan), 9 (Gejiu of Yunnan), and 10 (Zhaotong of Yunnan) are less than 0.85. The third group differs from the former two groups greatly.

Xu et al. [35] studied the HPLC FPS of Ma Huang herbs. Ma Huang is the stem of Ephedra sinica Stapf, E.intermedia Schrenk et C. A. Mey, and/or E.equisetina Bage. Twenty-two samples were collected from different regions of Gansu and inner Mongolia, in which S1 ~ S16 are Ephedra sinica Stapf generated from Gansu province, S17 ~ S20, S22 are E. intermedia Schrenk et C. A. Mey originated from Gansu province, and S21 are Ephedra sinica Stapf coming from inner Mongolia. These samples were treated with concentrated ammonia water and then extracted with ethyl ether. The FPS of these extracts were measured. The common model was established based on the FPS of sample 1 ~ 16 from Gansu province. Similarities of these samples were calculated referenced to the common model. The similarities of these samples are in the range of 0.955 ~ 0.998, which present that samples 1 ~ 16 are of excellent quality. The similarities of samples 17 ~ 22 were computed relative to the common model also; their similarities are 0.556, 0.669, 0.555, 0.828, 0.876, and 0.456 corresponding to samples 17 ~ 22, which show great varieties between samples 17–22 and 1–16.

The HPLC FPS of 9 leaf samples of different Shan Zha species were studied by Liu Rong Hua and his coworkers [36]. The FPS of components of these 9 samples extracted with 80 percent of methanol were carried out. The overlapping ratios of these samples were computed. The overlapping ratios were in the range of 0.82 ~ 0.96. There are significant differences between Dan Zi Shan Zha (Crataegus monogyna Jacq.), Yunnan Shan Zha (Crataegus scabrifolia (Franch.) Rehd.), Shan li hong (Crataegus pinnatifida Bge. var. major N. E. Br.), and Wild Shan Zha (Crataegus cuneata Sieb. & Zucc.). The overlapping ratios are arranged from 60 to 70 percent. Yunnan Shan zha was similar to Dan Zi Shan Zha obtained from Germany. The overlapping ratios were ranged from 85 to 88 percent. The similarities of Dan Zi Shan Zha related to Shan Li hong was in the range of 74 ~ 84 percent, and that of Yunnan Shan Zha compared with Shan Li Hong was in the range of 68 to 80 percent.

Cai et al. [37] investigated the HPLC FPS of 10 samples of rhizomes of Gymnadenia conopsea R. Br., No. 1 (Jingchuan, Sichuan), 2 (Kangding I, Sichuan), 3 (Kangding II, Sichuan), 4 (Wenchuan, Sichuan), 5 (Anguo, Hebei), 6 (Qinghai I), 7 (Qinghai II), 8 (Tibet I), 9 (Tibet II), 10 (Nepal), using HPLC-DAD-MSn technique. The HPLC FPS of components of these samples extracted with methanol were established. To standardize the fingerprint, 10 samples of rhizomes of G. conopsea were analyzed. Peaks that existed in all 10 samples were assigned as “characteristic peaks” for rhizomes of G. conopsea. There are 7 characteristic peaks (from peak 1 to peak 7) in the fingerprint. Peaks 2 and 3 were chosen as markers to match peaks, and peak 2 was chosen to calculate the relative retention time (RRT) and relative peak area (RPA) of each characteristic peak related to the reference peak. The similarities of these samples were analyzed based on the RRT and RPA by means of Cosine value of vectorial angles, in which the mean chromatogram is taken as a representative standard fingerprint for the chromatograms of the 10 samples. On the other hand, the 7 common peaks were identified, which are adenosine, 4-hydroxybenzyl alcohol, 4-hydroxybenzyl aldehyde, dactylorhin B, loroglossin, dactylorhin A, and militarine from peak no. 1 to 7.

6. Fingerprint Spectra Invariableness Analysis

Currently the identification and quality evaluation of herbal medicine mainly rely on many kinds of pattern recognitions, which are divided into two different classes: the first is the unsupervised method, the second is supervised one. The unsupervised methods do not depend on experiences, in which complex samples are classified by analyzing the experiment data directly. But the disadvantage to the unsupervised methods is that there are no ways to judge which samples belong to one class. For supervised methods the conclusions are obtained based on some parameters or coefficients established by studying some standard samples; thus the samples can be classified to different class samples. However, there is uncertainty in the determination of the so-called standard samples.

Because of these limitation in construction of existed pattern recognitions, it is essential to put forward new approach for correct identification of samples suitable for specific conditions. Zou et al. [38] proposed an approach named as the combinational numeral fingerprint spectra invariableness method, with which Glycyrrhiza herbal medicines can be classified based on the absolute parameter—invariableness. This method calculates the invariableness between inner group samples and inter group samples of the same kind, which is able to represent the characteristic properties of one kind of sample and is chosen as the absolute coefficient belonging to this kind of samples. The HPLC FPS of components of 10 planted or wild Glycyrrhiza samples of different species, collected from different areas and extracted with ethanol, were analyzed with this method. The results reveal that these Glycyrrhiza herbs can be evaluated well by means of this method.

7. Concluding Remarks

Quality control of TCM is becoming essential. This paper presented the different methods applied in analyzing HPLC FPS of herbal medicines which proved efficient and reliable for identifying and evaluating herbal medicines. Most of these other techniques are of qualitative approaches, which are unable to judge whether they are identical. However, the fingerprint spectra, invariableness offers good parameter to decide which herbal medicines are of the same quality or otherwise. We suggest the establishment of a database for these herbal medicines studied using HPLC FPS technique to be as a reference in quality control laboratories and pharmaceutical establishments dealing with herbal medicines.

References

H.-B. Zou, G.-S. Yang, Z.R. Qin, W.-Q. Jiang, A.-Q. Du, and H. Y. Aboul-Enein, “Progress in quality control of herbal medicine with IR fingerprint spectra,” Applied Spectroscopy Review, vol. 38, no. 9, pp. 1457–1475, 2005.

H.-B. Zou, J.-R. Yuan, and H. Yuan, “The historical development of technique-method in quality-control of Chinese materia medica,” Chinese Traditional Patent Medicine, vol. 25, no. 9, pp. 4–6, 2003.

Y. Hu, M.-L. Wang, G.-F. Qiu, S.-C. Liang, J.-Z. Wang, and X.-M. Hu, “Determination of the fingerprint of poria peels by high performance liquid chromatography,” Journal of Analytical Science, vol. 22, no. 6, pp. 636–640, 2006.

X. Y. Li, H. P. Pan, L. F. Yang, W. Q. Luo, G. H. Deng, and D. P. Wei, “Fingerprint of radix puerariae thomsonii by HPLC,” Chinese Traditional Patent Medicine, vol. 28, no. 9, pp. 1249–1253, 2006.

Z. T. Xie, Z. A. He, Y. C. Lou, and Y. W. Liu, “HPLC fingerprint of flavonoids in fruits of polygonum orientale,” Journal of Chinese Medicinal Materials, vol. 29, no. 10, pp. 1026–1028, 2006.

J.-W. Huang, R.-Z. Li, J. Liu, and H.-Y. Mai, “HPLC fingerprints of radix astragali of different sources,” Chinese Traditional Patent Medicine, vol. 27, no. 11, pp. 1244–1246, 2005.

Q. Wang, J. X. Wang, Z. G. Yu, X. Hu, and Y. H. Zhang, “Fingerprint of flos lonicerae by HPLC-FPC,” Chinese Traditional Patent Medicine, vol. 27, no. 7, pp. 751–754, 2005.

R. Shi, S. Y. Wang, W. L. Jiang, L. Nie, and Z. Hou, “Fingerprints of soybean total isoflavone by HPLC,” Chinese Traditional and Herbal Drugs, vol. 37, no. 2, pp. 202–205, 2006.

H. J. Dong, Z. J. Zhang, and J. Yu, “Chromatographic fingerprints of Andrographis paniculata (Burm.F.)Nees. Collected from different places,” Chinese Traditional Patent Medicine, vol. 28, no. 3, pp. 321–324, 2006.

D. Y. Li, T. T. Wang, X. H. Chen, and K. S. Bi, “Establishment of RP-HPLC fingerprint for quality assessment of Cortex Periplocae,” Journal of Chinese Medicinal Materials, vol. 29, no. 7, pp. 715–717, 2006.

L. Zhang, D. Wu, X. H. Chen, X. Wang, and K. S. Bi, “Quality assessment of RP-HPLC fingerprint for sophora flavescens Ait,” Chinese Journal of Pharmaceutical Analysis, vol. 26, no. 9, pp. 1261–1265, 2006.

D.-R. Xu, K.-C. Wang, J. Ding, and Z.-T. Wang, “Comparative studies on chromatograms of the fingerprints liposoluble constituents in radix salvia miltiorrhizae cultivated in different places,” Chinese Wild Plant Resources, vol. 25, no. 6, pp. 40–43, 2006.

M.-Z. Wu, Y. He, L.-Y. ang, and Z.-J. Wang, “Clustering analysis of HPLC chromatographic fingerprints of Paeonia suffruticosa,” China Journal of Chinese Materia Medica, vol. 32, no. 11, pp. 1054–1056, 2007.

R. Yu, B. Ye, C. Yan et al., “Fingerprint analysis of fruiting bodies of cultured Cordyceps militaris by high-performance liquid chromatography-photodiode array detection,” Journal of Pharmaceutical and Biomedical Analysis, vol. 44, no. 3, pp. 818–823, 2007.

M. J. Chen, H. B. Qu, and Y. Y. Cheng, “Identifying the authenticity of Chinese medicinal material with chemical fingerprint features,” Chemical Journal of Chinese Universities, vol. 24, no. 12, pp. 2181–2185, 2003.

M. J. Chen, Y. J. Wu, X. H. Fan, and Y. Y. Cheng, “Identification of the habitat of Ligusticum chuangxiong with chromatographic fingerprinting,” China Journal of Chinese Materia Medica, vol. 28, no. 7, pp. 606–610, 2003.

Y. Zhao, Y.-Z. Liang, L.-Z. Yi, P.-S. Xie, and Yang H. Yang H., “Application of chemical pattern into recognition of Zhishi (fructus aurantii immaturus),” Research and Practice of Chinese Medicines, vol. 2004, no. 18, pp. 70–73, 2004.

P. Xie, S. Chen, Y.-Z. Liang, X. Wang, R. Tian, and R. Upton, “Chromatographic fingerprint analysis—a rational approach for quality assessment of traditional Chinese herbal medicine,” Journal of Chromatography A, vol. 1112, no. 1-2, pp. 171–180, 2006.

J.-Y. Yang, B. Y. LI, Y.-Z. Liang, Q.-S. Xu, and P.-S. Xie, “Evaluation of chromatographic fingerprint of herbal medicine based on principal sensitivity vector regression,” Computers and Applied Chemistry, vol. 22, no. 4, pp. 282–286, 2005.

L.-Z. Yi, P.-S. Xie, Y.-Z. Liang, Y. Zhao, and H.-M. Lu, “HPLC specific (fingerprint) used for quality control of tangerine peel,” Chinese Journal of Pharmaceutical Analysis, vol. 26, no. 7, pp. 918–922, 2006.

L.-Z. Yi, D.-L. Yuan, Y.-Z. Liang, P.-S. Xie, and Y. Zhao, “Quality control and discrimination of Pericarpium Citri Reticulatae and Pericarpium Citri Reticulatae Viride based on high-performance liquid chromatographic fingerprints and multivariate statistical analysis,” Analytica Chimica Acta, vol. 588, no. 2, pp. 207–215, 2007.

Z. Wu, M. Zhang, C.-F. Zhang, and Z.-T. Wang, “Study on quality evaluation for 36 samples of radix polygonui multiflori by HPLC-fingerprints,” Chinese Pharmaceutical Journal, vol. 41, no. 4, pp. 257–260, 2006.

F.-D. Hu, J.-X. Zhao, S.-L. Feng, X. Liu, and J.-W. Xu, “Studies on chromatography fingerprint of huangqi by HPLC,” Journal of Chinese Medicinal Materials, vol. 27, no. 11, pp. 831–834, 2004.

Y.-J. Wu, X.-R. Hou, and Y.-Y. Cheng, “The research on chromatography fingerprint of Sarcandra glabra thunb,” China Journal of Chinese Materia Medica, vol. 30, no. 1, pp. 67–69, 2005.

M. Song, T.-J. Hang, and Z.-X. Zhang, “Fingerprints of Salvia miltiorrhiza water-soluble components by HPLC compared with fingerprint reference substance,” Chinese Traditional and Herbal Drugs, vol. 36, no. 3, pp. 360–364, 2005.

L. Jiang, X.-J. Li, and X.-G. Jia, “HPLC fingerprint chromatogram of radix arnebiae,” Chinese Traditional Patent Medicine, vol. 27, no. 11, pp. 1241–1244, 2005.

Y.-F. Chai, G.-A. Luo, S. Huang, and Z.-Y Lou, “Study on chromatographic fingerprints of rhizoma anemarrhenae,” Chinese Journal of Analysis Laboratory, vol. 4, no. 7, pp. 1–6, 2005.

Y.-M. Fu, L.-W. Zhang, Z.-F. Wu, G.-L. Xu, and X.-H. Liu, “Study on feature HPLC fingerprint spectra of Pericarpium Citri reticulatae,” Chinese Traditional Patent Medicine, vol. 28, no. 1, pp. 8–10, 2006.

C. Yu, Y. Yang, S.-Y. Liu, Z. C. Bai, X.-M. Zhang, and T.-T. Wang, “Fingerprint of rhizoma rtractylodis macrocephalae by HPLC,” Chinese Traditional and Herbal Drugs, vol. 37, no. 5, pp. 766–769, 2006.

C. Yu, S.-Y. Liu, J-A Fan, Z.-C. Bai, Y. Yang, and X.-M. Zhang, “The fingerprint of Paeonia suffruticosa Andr. by HPL,” Chinese Traditional Patent Medicine, vol. 37, no. 5, pp. 766–769, 2006.

X.-L. Wang, M. Cai, Y. Zhou, and L.-S. Ding, “HPLC fingerprint and HPLC-MS/MS analysis for the aerial parts of Saussurea involucrate,” Natural Product Research and Development, vol. 18, pp. 624–627, 2006.

T. Fan, Y. Wangm, K. Guo, and H.-M. Wen, “Study on the HPLC fingerprints of Glycyrrhiza uralensis fisch. Produced in inner mongolia,” Traditional Chinese Drug Research & Clinical Pharmacology, vol. 18, no. 1, pp. 44–46, 007.

L. Li, H.-G. Zhang, Y.-K. Sun, and Y.-J. Qiao, “Study on HPLC fingerprint of smilacis rhizoma,” China Journal of Traditional Chinese Medicine and Pharmacy, vol. 22, no. 4, pp. 206–208, 2007.

M.-L. Tian, F. Yi, Y.-Z. Niu, F. Liu, and Y.-B. Huang, “Preliminary study on quality fingerprint of radix aconiiti lateralis preparata by HPLC method,” Southwest China Journal of Agricultural Sciences, vol. 20, no. 3, pp. 521–524, 2007.

A.-X. Xu, B. Ge, P.-S. Song, and Z.-M. Zhang, “HPLC fingerprint of Herba Ephedrae from Gansu province,” Chinese Journal of Pharmaceutical Analysis, vol. 27, no. 4, pp. 513–517, 2007.

R.-H. Liu and B.-Y. Yu, “HPLC fingerprint chromatogram of leaves of Hawthorn,” Chinese Traditional Patent Medicine, vol. 29, no. 1, pp. 7–11, 2007.

M. Cai, Y. Zhou, S. Gesang, C. Bianba, and L. S. Ding, “Chemical fingerprint analysis of rhizomes of Gymnadenia conopsea by HPLC-DAD-MSn,” Journal of Chromatography B, vol. 844, no. 2, pp. 301–307, 2006.

H. Zou, G. Yang, A. Du et al., “Combinational numeral fingerprint spectra of Glycyrrhiza and analysis of common peak ratio invariableness in HPLC,” Biomedical Chromatography, vol. 20, no. 6-7, pp. 642–655, 2006.