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Systematic chemical analysis of flavonoids in the Nelumbinis stamen.

ABSTRACT

The stamen of lotus, known as Nelumbinis stamen, has been used as the folk medicine and functional food for a long time, which showed good activities of anti-ulcer, anti-thrombosis, analgesic, anti-diarrhea, strengthen uterine contraction. The bioactivities of Nelumbinis stamen were attributed to the existence of flavonoids, its characteristic chemical constituents. A reliable method for comprehensive chemical analysis of flavonoids in Nelumbinis stamen by HPLC-DAD-MS was developed for the first time. The extraction protocol of flavonoids from Nelumbinis stamen was optimized by an orthogonal design. The chromatographic conditions were optimized, which exhibited similar level than that of the UHPLC platform allowing target compound identification in a shorter time with little solvent consumption. Moreover, similarity analysis, hierarchical clustering analysis and principal components analysis were successfully applied to demonstrate the variability of these Nelumbinis stamen samples.

Keywords:

Nelumbinis stamen

Flavonoids

HPLC-DAD-MS

Chemometrics

Quality evaluation

Introduction

Traditional Chinese medicine (TCM) has played an important role in prevention and treatment of human diseases for thousands of years, and it was also widely used as functional food with potential health benefits (Chen, 1999). The sophisticated chemical constituents in TCM are the material basic of therapeutic effect and healthy function. Hence, chemical constituent evaluation in TCM is an essential part to the holistic research of TCM complex systems. Nowadays, quantitative analysis of multiple characteristic chemical makers coupled with qualitative analysis of chromatographic fingerprinting provide a promising approach for effective and systematic evaluation of chemical constituents in TCM complex systems (Liang et al., 2004; Fan et al., 2006; Tistaert et al., 2011).

Lotus (Nelumbo nucifera Gaerten), is a perennial aquatic herb that has been cultivated for more than 2000 years, which is distributed widely throughout East Asia, Australia and North America (Guo, 2009). It exhibits good traditional efficacy and medicinal application in China with a long history. All of the tissues of N. nucifera, including the folium, plumula, semen, receptaculum and rhizomatis nodus, are used as folk medicines with different traditional efficacy and medicinal application, respectively, and all of them are recorded in Chinese Pharmacopoeia (2010 Version). The stamen of N. nucifera is usually used for the treatment of seminal emission, spermatorrhea, excessive leucorrhea and frequent urination, and shows the effect of strengthening the kidney and arresting seminal emission. The folium of N. nucifera is used for the treatment of dire thirst caused by summer-heat with dire thirst, diarrhea caused by summer-damp or deficiency of the spleen, abnormal uterine bleeding caused by heat in blood and so on. The plumula of N. nucifera is usually used for the treatment of impaired consciousness and delirium due to invasion of the pericardium by heat. The semen of N. nucifera is usually used for the treatment of protracted diarrhea due to hypofunction of the spleen, leukorrhagia, palpitation and insomnia. The receptaculum of N. nucifera is usually used for the treatment of abnormal uterine bleeding and lochiorrhea due to blood stagnation after child birth. The rhizomatis nodus of N. nucifera is usually used for the treatment of hematemesis, bleeding from five sense organs or subcutaneous tissue and hematuria (Chinese Pharmacopeia Commission, 2010). Owing to its efficacy, Nelumbinis stamen is usually used together with other medicinal materials to compose TCM prescriptions in China. For example, Nelumbinis stamen is the main ingredient of the prescriptions "Jin-suo-gu-jing-wan", "Zhi-zuo-gu-ben-wan" and "Lian-shen-tang", etc. (Deng, 2000; Wang and Wang, 2009). These prescriptions are recorded in the ancient herbal books, which are widely used at TCM hospitals now, and show good clinical efficacy.

Existing results showed flavonoids were the characteristic chemical constituents of Nelumbinis stamen, which exhibited various bioactivities including anti-ulcer, anti-thrombosis, analgesic, anti-diarrhea, strengthen uterine contraction and so on (Zhang et al., 1998; Wu et al., 2003; Zhou et al., 2011). Spectrophotometry, thin layer chromatography, capillary zone electrophoresis with ultraviolet detection and high performance liquid chromatography were the methods used for quality control of Nelumbinis stamen, but the majority of studies were limited to quantitative analysis of little marker compounds in the lotus stamen (Shu et al., 2011; Yang and Zhao, 2011; Jing et al., 2007; Men et al., 2003). Moreover, the chemical quality evaluation of Nelumbinis stamen in Chinese Pharmacopoeia (2010 Version) is still in a blank, so it is necessary to develop an effective method to evaluate its quality accurately and systematically.

An accurate, rapid and systematic high performance liquid chromatography coupled with diode array detection and mass spectrometry (HPLC-DAD-MS) of multiple flavonoids determination in combination with chromatographic fingerprint analysis was developed for chemical quality evaluation of Nelumbinis stamen. The extraction protocol was optimized by an orthogonal experimental design. 11 flavonoids were identified and determined simultaneously. Furthermore, similarity analysis (SA), hierarchical clustering analysis (HCA) and principal components analysis (PCA) were successfully applied to demonstrate the variability of the 11 flavonoids in the 14 batches of Nelumbinis stamen collected from different localities. Multiple kinds of statistical analysis software were successfully applied to data mining to make the results more accurate and reliable.

Materials and methods

Chemical and materials

Eight flavonoid glycosides and three aglycones were obtained from Phytomarker Ltd. (Tianjin, China). Acetonitrile were purchased from Floneywell Burdick & Jackson (Muskegon, USA). Analytical grade of methanol was purchased from Beijing Chemical Works (Beijing, China). Formic acid, acetic acid and phosphoric acid (HPLC grade) were obtained from Tianjin Guang Fu Fine Chemical Research Institute (Tianjin, China). Pure water (18.2 M[ohm]) for the HPLC analysis was obtained from a Milli-Q System (Millipore, Billerica, MA, USA).

Plant samples

14 batches of Nelumbinis stamen samples were collected from different localities of Jianning County in Fujian province of China. All air-dried samples were ground and sieved (65-mesh), respectively. A sample (1.0000g) was suspended with 60ml methanol in a capped conical flask, weighed accurately, and reflux-extracted twice (1 h for each time). The combined extracts were evaporated to 10-15 ml in a rotary evaporator. The residue was transferred to a 25 ml volumetric flask with methanol, and then added methanol to the mark after cooling to room temperature. The sample solution was filtered through a 0.22 [micro]m membrane filter prior to injection into the HPLC system.

HPLC methods

Chromatographic analysis was performed on an Agilent 1260 HPLC system coupled with diode array detector (Agilent Technologies, Palo Alto, CA, USA). Chromatographic data were processed by Agilent Chem Station software. Chromatographic separation was performed on a Poroshell 120 C18-column (100 mm x 4.6 mm, 2.7 [micro]m, Agilent, CA, USA). The mobile phase consisted of 0.7% acetic acid in water (A) and methanol (B), and the flow rate was at 0.6ml/min. The eluting conditions were optimized as follows: 0-26min at 15% B; 26-30min from 15 to 31% B; 30-35min from 31 to 35% B; 35-42 min at 35% B; 42-45 min from 35 to 90% B and 45-50 min at 90% B with re-equilibration of the column at 50-52 min from 90 to 15% B, and 52-60 min at 15% B. Chromatograms were acquired at 360 nm and diode array spectra were recorded from 210 to 600 nm. The column temperature was maintained at 36 [degrees]C and the injection volume was 2 [micro]l.

Identification of flavonoids

HPLC-DAD-MS analysis was carried out with Applied Biosystem 3200 Q-Trap mass spectrometer (Foster City, CA, USA) connected to an Agilent 1200 HPLC system via electrospray ionization interface. The chromatographic conditions were as described above. Electrospray ionization was applied in negative ion mode for MS and MS/MS to give fragmentation information on the molecular weights and aglycone groups. The mass spectrometers were optimized in negative ion mode with an ion spray voltage of4000 V, curtain gas of 10 psi, nebulizer gas of 60 psi and auxiliary gas 40 psi. The ion source temperature was set at 400 [degrees]C. Ultrapure nitrogen was used as nebulizer, heater, curtain and collision-activated dissociation (CAD) gas. Data were processed by the Analyst 1.4 software (Applied Biosystems/MDSSciex). MS data, retention time and UV-Vis spectra were used to identify the flavonoids contained in Nelumbinis stamen. The assignments were validated by co-elution with the corresponding standards and comparison with the published data.

Preparation of standard solutions and method validation

Each standard was accurately weighed, dissolved in methanol, and the standard solutions were then diluted to generate an appropriate concentration range to establish calibration curves. All calibration curves were constructed by using five different concentrations of each standard in triplicate. Analytical method was validated for the calibration curves, limit of detection and quantitation (LOD and LOQ), repeatability, stability, and accuracy of the 11 flavonoids.

Optimization of flavonoids extraction

Optimization of flavonoids extraction conditions from Nelumbinis stamen was studied via an orthogonal ([L.sub.9] [3.sup.4]) experimental design, including three methanol concentrations at 70%, 90% and 100% (v/v), three solvent to sample ratios [20:1, 40:1, 60:1 (v/w)], three different extraction time (0.5 h, 1 h, 1.5 h), and three extraction cycles (1, 2, 3 cycles). Each extract combination was tested in triplicate, and the optimized extraction conditions were as described in 'Plant samples'.

Chemometrics analysis

Similarity analysis was performed by the Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine (Version 2004A), which was recommended by China's State Food and Drug Administration (CFDA). The hierarchical clustering analysis (HCA) and principal components analysis (PCA) were applied to demonstrate the variability of the content of 11 flavonoids in 14 batches of Nelumbinis stamen samples by using PASW Statistics (Version 19.0), Matlab (Version 2012a) and the Unscrambler X 10.0 software from Camo AS (Trondheim, Norway).

Results and discussion

Optimization of HPLC conditions

Different chromatographic columns were investigated: Agilent Eclipse XDB-C18 (250 mm x 4.6 mm, 5 [micro]m), Agilent Zorbax SB C18-column (250 mm x 4.6 mm, 5[micro]m), and Agilent Poroshell 120 C18-column (100 mm x 4.6 mm, 2.7 [micro]m). The resolution of chromatographic peaks of the first two columns was not very well, and it took much more time and chromatographic solvent. The best separation efficiency and the shortest analysis time were achieved by using Poroshell 120 C18-column.

Methanol-water and acetonitrile-water were tested as mobile phase to optimize the separation condition, and the latter was chosen. Because compounds 1 and 2 were eluted together as an overlapping peak in methanol-water system, and acetonitrile-water system showed better resolution, peak shape and stable baselines as well as lower column back pressure compared with methanol-water system. In addition, different concentrations of formic acid and acetic acids were compared as an additive to improve the separation efficiency, and it was found that 0.7% acetic acids achieved the best separation and suppressed the tailing of the peaks.

The column temperature and flow rate were optimized, which had significant impact on the separation. Best separation was achieved in the column temperature at 36[degrees]C and flow rate at 0.6 ml/min. Of the characteristic UV spectrum pattern of flavonoids (band I, [[lambda].sub.max] around 300-380 nm and band II, [[lambda].sub.max] around 240-280 nm), the stronger and more specific band I at 360 nm was selected to monitor the chromatograms (Mabry et al., 1970).

The optimized chromatographic conditions of flavonoids from Nelumbinis stamen were as described in 'HPLC methods', which enabled acceptable resolution of compounds 1 and 2 as well as excellent resolution of compounds 3-11 (Fig. 1). The separation efficiency of Agilent 1260 combined with Agilent Poroshell 120 C18-column (100 mm x 4.6 mm, 2.7 [micro]m) exhibited similar level than that of the UHPLC platform allowing target compound identification in a shorter time with little solvent consumption.

Validation of quantitative analysis method

The calibration curves were constructed by five concentration assays of each standard in triplicate. Regression equations, the correlation coefficients ([r.sup.2]), detection and quantification limits were listed in Table 1. The high correlation coefficients ([r.sup.2] > 0.9996) indicated good linearity in relatively wide concentration ranges for 11 flavonoids. The LODs and LOQs were less than 0.15 and 0.67 ([micro]g/ml, which were determined at a signal-to-noise ratio (S/N) of about 3 and 10, respectively.

The intra-day precision (six times per day) and inter-day precision (twice a day for four consecutive days) determinations were performed on samples and standard solutions, respectively. The results showed that the RSDs of the 11 flavonoids were less than 2.96% for inter-day precision, and less than 1.26% for intra-day precision. The low RSD values obtained for all 11 flavonoids confirmed the high repeatability and intermediate precision of the developed method (Table 2). Stability of sample solution was tested at the time interval of 0, 8, 16, 24, 32, 40 and 48 h under room temperature, and the sample solution were found to be rather stable in methanol within 48 h (RSD <2.85%). Six independently prepared samples were analyzed to validate the repeatability of the method. This assay had good repeatability with RSD less than 2.00% (Table 2).

Recovery test was carried out to further investigate the accuracy of the method by adding three concentration levels of the mixed standard solutions to known amounts samples. The resultant samples were then extracted and analyzed by using the proposed procedure. As shown in Table 2, the recoveries obtained in this study ranged from 94.10% to 98.02%, which demonstrated that the analytical method developed in this study showed high accuracy, and the low RSDs of all standards (<2.08%) also indicated good reproducibility.

HPLC-DAD-MS identity confirmation

The identity of chromatographic peaks in the sample HPLC profiles was confirmed by comparing their spectra with those of the reference compounds at same retention time. Spiking sample with standard mixtures performed a further confirmation assay by HPLC-DAD-MS experiment. The retention time, maximum ultraviolet absorption and mass spectral data of compounds exactly matched with the corresponding reference compounds, which were shown in Table 3.11 chromatographic peaks in Nelumbinis stamen were unequivocally identified, namely rutin (1), hyperoside (2), isoquercitrin (3), kaempferol 3-O-galactoside (4), kaempferol 3O-glucuronide (5), astragalin (6), isohamnetin 3-O-rutinoside (7), isorhamnetin 3-O-glucoside (8), quercetin (9), kaempferol (10) and isorhamnetin (11). Their structures were shown in Fig. 1. The results further revealed that the 11 investigated flavonoids were the main chemical constituents of Nelumbinis stamen and covered more than 90% of the total peak areas, which was of great importance to establish a relatively accurate and comprehensive method for its quality evaluation.

Optimization of extraction procedures

Based on the preliminary optimized results of single-factor experimental design, three levels of each factor were selected. The parameters obtained from the orthogonal ([L.sub.9] [3.sup.4]) test of the flavonoid extraction were weighted and quantitatively analyzed using evaluation indices k and R. Kaempferol 3-0-galactoside (4) was dominant compound found in Nelumbinis stamen. Statistical analysis was therefore carried out separately for its content and the total amount of the other flavonoids. Extraction cycle was the most important factor among the four studied factors. Solvent had much less significant effects on the yield of flavonoids. Based on the R values, the factors can be ranked by the importance for extracting both kaempferol 3-O-galactoside (4) and the other flavonoids in Nelumbinis stamen as follows: extraction cycles > solvent-to-sample ratio > extraction time > solvent. Based on the k values, the optimized extraction procedures were as described in 'Plant samples'.

Sample analysis

Quantitative analysis

The newly developed method was subsequently applied to quantitative analysis of 11 flavonoids in 14 batches of Nelumbinis stamen samples collected from different localities. Each sample was analyzed three times to determine the mean content (mg/100g) and the results were shown in Table 4. The results indicated that the content of 11 flavonoids varied greatly among the samples collected from different localities, and the total content of 11 flavonoids was higher in SI, S6 and SI3, and lower in S4, S9, SI 1, SI2 and S14. 11 flavonoids were identified and quantified simultaneously, and they covered more than 90% of the total peak areas which could provide a relatively comprehensive quality evaluation for Nelumbinis stamen. The established method was simple, accurate and economic for quality evaluation of the Nelumbinis stamen.

[FIGURE 2 OMITTED]

Similarity analysis

To evaluate the similarities of these samples, Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine (Version 2004A) was performed based on their HPLC fingerprints. 15 peaks existing in all 14 batches of Nelumbinis stamen samples were assigned as "characteristic peaks". The similarities of the chromatograms of 14 batches of samples were compared to the refer fingerprint "R". The closer the cosine values approached 1, the more similar the two chromatograms were. Similarity analysis was therefore conducted based on the refer fingerprint. The similarity values of 14 samples were more than 0.95, except for S4, S9, S11, S12 and S14. These meant that 9 batches of Nelumbinis stamen samples showed good similarity on chemical constituents. The samples with lower similarity value showed poor consistency, which might not meet medicinal requirements. Therefore, chromatographic fingerprint combined with similarity analysis was an efficient method to judge the consistency of samples.

Hierarchical cluster analysis

In order to validate the results of similarity analysis and further elucidate the resemblance relationship among samples, hierarchical cluster analysis (HCA) was applied by PASW Statistics, Matlab and the Unscrambler X 10.0 software. The results of HCA clearly showed that total 14 samples were divided into two clusters obviously (Fig. 2). Group I was formed by the samples S4, S9, S11, SI 2 and S14. Group II consisted of the remaining samples. The result was very similar to the similarity analysis of their chromatograms, and HCA was helpful to differentiate the origin of samples and judge the consistency of Nelumbinis stamen.

Principle component analysis

In order to evaluate the discrimination ability of these 11 flavonoids, principle component analysis (PCA) was employed using the relative peak areas of the 11 peaks as input data instead of the full spectrum of fingerprints without any preprocessing by using Matlab and the Unscrambler X 10.0 software. The results of PCA's loading plot obtained by two kinds of different statistical software further revealed that compounds 1, 4, 6 and 10 might have more influence on the discrimination of the samples from different localities than other compounds (Fig. 2). Moreover, the content of four flavonoids was accounted for the higher content in Nelumbinis stamen. Hence, compounds 1, 4, 6 and 10 could be chosen as the chemical markers for evaluating the quality of Nelumbinis stamen. The loading plot obtained by two kinds of different statistical software showed good consistency and made the results more accurate and credible.

Conclusions

In this study, Agilent 1260 combined with Poroshell 120 C18-column (100 mm x 4.6 mm, 2.7 [micro]m) exhibited higher separation efficiency allowing target compounds identification in a shorter time. This platform did not require rather expensive instruments and chromatographic columns, exhibited higher cost-efficiency. Meantime, this platform consumed less chemical solvents, which it was helpful to protect the atmospheric environment. Hence, we selected this platform for evaluating the quality of Nelumbinis stamen. In addition, multiple kinds of statistical analysis software were successfully applied to data mining to make the results more accurate and reliable.

A reliable method for comprehensive chemical analysis of flavonoids in Nelumbinis stamen by HPLC-DAD-MS was developed for the first time. The validated method was successfully applied to qualitative and quantitative analysis of 14 batches of Nelumbinis stamen samples collected from different localities. Similarity analysis and hierarchical cluster analysis were successfully applied to differentiate the origin of samples and judge the consistency of samples. Moreover, rutin (1), kaempferol 3-0-galactoside (4), astragalin (6), and kaempferol (10) were deemed to the main chemical markers in Nelumbinis stamen according to the results of principle component analysis, which could be helpful to further evaluate the quality of Nelumbinis stamen. So, it is demonstrated that quantitative analysis of multiple characteristic chemical makers coupled with qualitative analysis of chromatographic fingerprinting is a powerful, practical tool for comprehensive quality analysis of Traditional Chinese medicine.

ARTICLE INFO

Article history:

Received 16 July 2014

Received in revised form 17 August 2014

Accepted 13 September 2014

References

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Chinese Pharmacopeia Commission, 2010. Pharmacopoeia of the People's Republic of China Version. Chinese Medical Science and Technology Press, Beijing.

Deng, T.T., 2000. Dengtietao Yi Ji. People's Medical Publishing House, Beijing.

Fan, X.H., Cheng, Y.Y., Ye, Z.L., Lin, R.C., Qian, Z.Z., 2006. Multiple chromatographic fingerprinting and its application to the quality control of herbal medicines. Anal. Chim. Acta 555, 217-224.

Guo, H.B., 2009. Cultivation of lotus (Nelumbo nucifera Caertn. ssp. nucifera) and its utilization in China. Genet. Resour. Crop Evol. 56, 323-330.

Jing, R.J., Jiang, X.Y., Hou, S.R., Li, X.J., Yuan, Z.B., 2007. Determination of quercetin, luteolin, kaempferol and isoquercitrin in stamen nelumbinis by capillary zone electrophoresis-ultraviolet detection. Chin. J. Anal. Chem. 35, 1187-1190.

Liang, Y.Z., Xie, P., Chan, K., 2004. Quality control of herbal medicines. J. Chromatogr. B 812, 53-70.

Mabry, T.J., Markham, K.R., Thomas, M.B., 1970. The Systematic Identification of Flavonoids. Springer, New York, pp. 41-43.

Men, X.S., Sha, M., Cao, A.M., Jiang, L., Deng, T.H., 2003. Determination of quercetin and kaempferol in Stamen nelumbinis by HPLC. Chin. Tradit. Plant Med. 25, 58-60.

Shu, B.H., Shu, C.Y., Sun, J., 2011. Determination of total flavone in Stamen Nelumbinis by spectrophotometry. Inform. Tradit. Chin. Med. 28, 81-82.

Tistaert, C., Dejaegher, B., Vander, H.Y., 2011. Chromatographic separation techniques and data handling methods for herbal fingerprints: a review. Anal. Chim. Acta 690, 148-161.

Wang, A., Wang. J., 2009. Yi Fangji Jie. China Press of Traditional Chinese Medicine, Beijing.

Wu, LM., Qiu, G.Q., Chen, L.J., Zhang, J.Z., Zhuang, Z.X., 2003. Experiment of effects of Stamen Nelumbins on uterine contractivity in different animals, j. Mod. Clin. Med. Bioeng. 9, 166-167.

Yang, B., Zhao, X.X., 2011. Study on TLC identification for Nelumbinis stamen. Cap. Med. 12, 1256-1257.

Zhang, M.F., Shen, Y.Q., Zhu, Z.P., Wang, H.W., 1998. Anti-thrombotic, anti-ulcerative and analgesic actions of Stamen Nelumbins. Res. Tradit. Chin. Med. 14, 16-18.

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Jiushi Liu (a), Yaojie Guo (a), Jin Zhang (3), Yaodong Qi (a), Xiaoguang Jia (b), Gangfeng Gao (c), Jingao Shuai (d), Haitao Liu (a,b,) *, Bengang Zhang (a), **, Peigen Xiao (a)

(a) Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine (Peking Union Medical College), Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100193, China (b) Xinjiang Institute of Chinese and Ethnic Medicine, Urumqi 830002, Xinjiang, China

(c) Bio-Medicine and Bio-Industry Office in Sanning City, Sanning 365000, Fujian Province, China

(d) Fujian Wenxin Lianye Food Co. Ltd.Jianning 354500, China

* Corresponding author at: Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine (Peking Union Medical College), Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100193, China.

Tel.: +86 10 57833196; fax: +86 10 57833196.

** Corresponding author. Tel.:+86 10 57833191; fax:+86 10 57833196.

E-mail addresses: htliu0718@126.com (H. Liu), bgzhang@implad.ac.cn (B. Zhang).

http://dx.doi.Org/10.1016/j.phymed.2014.09.003
Table 1
Linearity, LODs and LOQs of 11 flavonoids.

Compounds      Calibration curve      [r.sup.2]     Linear range
                                                   ([micro]g/ml)

1             y = 4.9025x + 0.7364      0.9998      5.00-160.00
2             y = 7.8114x + 1.4609      0.9996       1.31-42.00
3             y = 8.7165x + 0.8196      0.9996      4.50-144.00
4             y = 5.5689x + 2.4302      0.9999      4.50-144.00
5             y = 3.8300x + 0.1866      0.9998       2.10-50.40
6             y = 6.3373x + 0.1686      1.0000      5.75-184.00
7             y = 6.7022x - 0.3084      0.9997       1.19-36.00
8             y = 7.7397x + 1.7078      1.0000      3.50-112.00
9            y = 11.9088x + 0.6269      0.9997      4.00-128.00
10           y = 17.6076x + 1.2788      1.0000      5.25-168.00
11           y = 13.0817x + 0.6551      0.9998       0.43-13.60

Compounds         LOD              LOQ
             ([micro]g/ml)    ([micro]g/ml)

1                 0.15             0.67
2                 0.10             0.46
3                 0.09             0.41
4                 0.15             0.67
5                 0.09             0.29
6                 0.13             0.58
7                 0.11             0.48
8                 0.12             0.53
9                 0.04             0.17
10                0.06             0.26
11                0.06             0.28

Note: y, peak area; x, compound concentration ([micro]g/mL);
LOD = limit of detection, S/N = 3; LOQ = limit of
quantitation, S/N = 10.

Table 2
Precision, stability, repeatability and recovery
of 11 flavonoids.

Compounds    Precisions (n = 6)        Repeatability
                                          (n = 5)
             Intra-day    inter-day       RSD (%)
              RSD (%)      RSD (%)

1               0.44         0.51           0.79
2               0.94         1.12           1.06
3               1.13         0.72           1.10
4               0.48         0.66           1.39
5               0.72         1.66           1.90
6               0.95         0.95           0.45
7               1.26         1.28           1.22
8               0.84         1.00           0.72
9               1.08         2.45           2.00
10              0.71         2.96           0.74
11              1.22         2.32           1.62

Compounds    Stability    Recovery    RSD (%)
              (n = 6)
              RSD (%)

1               0.50        94.10       1.18
2               1.28        95.14       1.21
3               1.07        95.34       1.55
4               0.67        96.36       1.43
5               1.70        94.77       1.45
6               1.00        96.31       1.32
7               1.12        95.11       1.38
8               0.86        97.56       1.28
9               2.08        97.27       0.98
10              2.85        98.02       1.67
11              2.15        94.75       1.86

Table 3
Identification of 11 flavonoids in the
Nelumbinis stamen.

Peak    Identification                 RT (min)    [[lambda]
No.                                                .sub.max] (nm)

1       Rutin                          10.37       254.7, 350.5
2       Hyperoside                     11.10       254.7, 354.1
3       Isoquercitrin                  12.12       254.7, 354.1
4       Kaempferol 3-O-galactoside     16.70       252.4, 354.1
5       Kaempferol 3-O-glucuronide     19.66       264.3, 346.9
6       Astragalin                     20.48       264.3, 346.9
7       Isorhamnetin 3-O-rutinoside    21.39       252.4, 354.1
8       Isorhamnetin 3-O-glucoside     23.94       252.4, 354.1
9       Quercertin                     34.07       254.7, 369.5
10      Kaempferol                     37.41       265, 366
11      Isorhamnetin                   38.23       252, 370

Peak    NI-                   MS/MS
No.

1       609.5[[M-H].sup.-]    301.5[[A-H].sup.-]
2       463.3[[M-H].sup.-]    300.3[[A-2H].sup.-]
3       463.4[[M-H].sup.-]    300.4[[A-2H].sup.-]
4       447.0[[M-H].sup.-]    284.1[[A-2H].sup.-]
5       461.1[[M-H].sup.-]    285.1[[A-H].sup.-]
6       477.1[[M-H].sup.-]    284.1[[A-2H].sup.-]
7       623.2[[M-H].sup.-]    315.1[[A-H].sup.-]
8       477.2[[M-H].sup.-]    314.0[[A-2H].sup.-]
9       301.2[[A-H].sup.-]
10      281.3[[A-H].sup.-]
11      317.3[[A-H].sup.-]

Table 4
Content (mg/100g) of 11 flavonoids in the Nelumbinis stamen
collected from different localities (n = 3).

No.    Origin               1        2        3         4        5

SI     Chenyu village     62.07    33.13    38.02    112.07    37.49
S2     Xianhe village     37.45    19.77    31.92     80.18    36.32
S3     Xiyuan village     41.59    21.50    23.49     96.77    23.63
S4     Shangli village    28.69     7.53     6.59     40.57     8.52
S5     Hedong village     38.78    23.09    33.54     99.07    30.35
S6     Dayuan village     58.32    32.02    42.65    114.75    38.99
S7     Qi village         44.19    17.66    17.69     73.19    21.55
S8     Xiuzhu village     32.77    29.90    31.53     84.56    26.28
S9     Liyuan village     31.09     4.35     6.76     21.77    11.51
S10    Lanxi village      38.82    24.49    33.62     85.24    24.87
S11    Shangli village    33.20     7.89    10.84     42.03    11.61
S12    Shangli village    29.88    10.84    11.97     46.41    14.67
S13    Chenyu village     37.94    27.67    42.66    119.39    29.73
S14    Shangli village    21.67     7.90    10.66     38.28    12.63

No.       6        7        8        9        10      11      Total

SI     123.67    25.56    45.24     9.87    38.15    4.88    530.14
S2     117.98    13.78    34.13     7.73    41.71    5.35    426.33
S3      80.96    14.97    27.62     8.57    38.21    6.37    383.68
S4      28.03     6.23     9.72     2.58    11.43    2.12    152.01
S5     115.85    17.06    37.79     6.53    31.13    4.13    437.33
S6     134.83    22.57    49.04    10.11    38.18    5.69    547.15
S7      56.79    13.41    24.85     8.45    42.82    9.11    329.71
S8     102.87    22.35    38.82    10.03    33.88    5.52    418.51
S9      23.81     4.67    10.55     4.21    21.43    3.55    143.72
S10     97.69    20.16    36.95     5.54    22.93    4.69    395.00
S11     40.65     8.01    15.00     2.74    12.83    1.23    186.03
S12     39.20     8.92    16.74     5.21    24.14    4.78    212.76
S13    138.82    19.97    47.19     4.86    20.36    2.06    490.65
S14     35.30     7.32    13.82     3.23    11.98    1.65    164.44

Fig. 1. Typical chromatogram for chemical analysis of
Nelumbinis stamen (A), mixed standards (B) and their
chemical structures.

NO.     R1        R2        R3

1       OH    O-Ara-Gal     OH
2       OH      O-Glu       OH
3       OH      O-Gal       OH
4       H       O-Gal       OH
5       H       O-GIn       OH
6       H       O-Glu       OH
7      OMe      O-Rut       OH
8      OMe      O-Glu       OH
9       OH        OH        OH
10      H         OH        OH
11      OH        OH       OMe
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Author:Liu, Jiushi; Guo, Yaojie; Zhang, Jin; Qi, Yaodong; Jia, Xiaoguang; Gao, Gangfeng; Shuai, Jingao; Liu
Publication:Phytomedicine: International Journal of Phytotherapy & Phytopharmacology
Article Type:Report
Date:Nov 15, 2014
Words:5000
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