Quantitative analysis and chemical fingerprint similarity for quality control of the seeds of Paeonia suffruticosa Andr. by HPLC

Xiao Tian , Meiqi Yang , Sen Guo , Qingchao Liu , Li Zhang , Chi-Tang Ho , Naisheng Bai

Chemical Research in Chinese Universities ›› 2017, Vol. 33 ›› Issue (4) : 546 -551.

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Chemical Research in Chinese Universities ›› 2017, Vol. 33 ›› Issue (4) : 546 -551. DOI: 10.1007/s40242-017-6463-9
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Quantitative analysis and chemical fingerprint similarity for quality control of the seeds of Paeonia suffruticosa Andr. by HPLC

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Abstract

According to the General Office of the State Council of China, tree peony seeds(TPSs, Paeonia suffruticosa Andr.) are considered an emerging source for edible oil. In Chinese folk medicine, TPSs are used for alleviating waist and leg pain. In the present study, a simple, accurate and rapid fingerprint method based on high performance liquid chromatography with diode array detection(HPLC-DAD) was developed and validated to quantify the profiles of ten representative compounds in TPSs. All standard calibration curves exhibited good linearity(R 2>0.9995) in the HPLC-DAD analysis. The recovery of the standards ranged from 96.37% to 102.10%. The results show that stilbenoids are the major constituents in TPSs, and their total content ranges from 25.71 mg/g to 54.03 mg/g. Suffruticosol A, suffruticosol B, trans-ε-viniferin, ampelopsin E and paeoniflorin are the major components in methanol-water(80:20, volume ratio) extracts with average contents of 3.962, 12.264, 5.826, 14.060 and 12.755 mg/g, respectively. Additionally, 14 batches of seeds collected from different regions were used to establish a reference fingerprint. Their similarity values were higher than 0.944 except for the sample(0.863) from Linxia. These results collectively indicate that the quantitative HPLC fingerprint method can serve as a prerequisite quality control for TPSs, and is a promising resource for developing new herbal or food products.

Keywords

Paeonia suffruticosa Andr. / Fingerprint / High performance liquid chromatography with diode array detection(HPLC-DAD) / Quality analysis / Similarity

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Xiao Tian, Meiqi Yang, Sen Guo, Qingchao Liu, Li Zhang, Chi-Tang Ho, Naisheng Bai. Quantitative analysis and chemical fingerprint similarity for quality control of the seeds of Paeonia suffruticosa Andr. by HPLC. Chemical Research in Chinese Universities, 2017, 33(4): 546-551 DOI:10.1007/s40242-017-6463-9

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References

[1]

Stern F. C., A Study of the Genus Paeonia, The Royal Hortic. Soc.

[2]

Zhou Z. Q. Genet. Resour. Crop. Ev., 2006, 53: 11.

[3]

He C. N., Peng Y., Xiao W., Liu H. B., Xiao P. G. Food Chem., 2013, 138: 2108.

[4]

Li J. J. Chinese Tree Peony and Herbaceous Peony, 1999, Beijing: China Forestry Publishing House, 16.

[5]

Li C., Du H., Wang L. S., Shu Q. Y., Zheng Y. R., Xu Y. J., Zhang J. J., Zhang J., Yang R. Z., Ge Y. X. J. Agric. Food Chem., 2009, 57(18): 8496.

[6]

Li S. S., Yuan R. Y., Chen L. G., Wang L. S., Hao X. H., Wang L. J., Zheng X. C. Food Chem., 2015, 173: 133.

[7]

Picerno P., Mencherini T., Sansone F., Gaudio P. D., Granata I., Porta A., Aquino R. P. J. Ethnopharmacol., 2011, 138(3): 705.

[8]

Lin H. C., Ding H. Y., Ko F. N., Teng C. M., Wu T. C. Planta Med., 1999, 65(7): 595.

[9]

Wu S. H., Wu D. G., Chen Y. W. Chem. Biodivers., 2010, 7(1): 90.

[10]

Okubo T., Nagai F., Seto T., Satoh K., Ushiyama K., Kano I. Biol. Pharm. Bull, 2000, 23(2): 199.

[11]

Yu H. P., Cheng F. Y., Zhong Y., Cai C. F., Wu J. H., Cui H. L. Scientia Horticulturae, 2013, 164(164): 58.

[12]

Mitchell S. H., Zhu W., Young C. Y. F. Cancer Res., 1999, 59(23): 5892.

[13]

Kim H. J., Chang E. J., Song J. B., Sun M. S., Park H. D., Chang H. R., Park J. H., Sang W. C. Arch. Pharm. Res., 2002, 25(3): 293.

[14]

Kim H. J., Chung S. K., Choi S. W. J. Food Sci. Nutr., 1998, 3(4): 315.

[15]

Kim H. J., Chang E. J., Cho S. H., Chung S. K., Park H. D., Choi S. W. Biosci. Biotechnol. Biochem., 2002, 66(9): 1990.

[16]

Kim H. J., Chung S. K., Choi S. W. J. Food Sci. Nutr., 1999, 4(3): 163.

[17]

Sarker S. D., Whiting P., Dinan L., Šik V., Rees H. H. Tetrahedron, 1999, 55(2): 513.

[18]

Zheng G., Yang D., Wang D., Zhou F., Yang X., Jiang L. J. Agric. Food Chem., 2009, 57(15): 6552.

[19]

Zou H. M., Zhou C., Sun C. J., Li Y. X., Yang X. S., Wen J., Zeng H. Y. Chem. J. Chinese Universities, 2016, 37(7): 1276.

[20]

Ding L., Li Y., Li M. J., Liu Z. Y., Zhang H. Q. Chem. J. Chinese Universities, 2003, 24(8): 1403.

[21]

Zhu H. Y., Meng X. Y., Bao Y. L., Yu C. L., Wu Y., Li Y. X. Chem. J. Chinese Universities, 2010, 31(4): 679.

[22]

Zhu S. L., Dou S. S., Liu X. R., Liu R. H., Zhang W. D., Huang H. L., Zhang Y., Hu Y. H., Wang S. P. Chem. Res. Chinese Universi-ties, 2011, 27(1): 38.

[23]

Uansiri S., Vichapong J., Kanchanamayoon W. Chem. Res. Chinese Universities, 2016, 32(2): 178.

[24]

Condori J., Sivakumar G., Hubstenberger J., Dolan M. C., Sobolev V. S. Plant Physiol. Bioch., 2010, 48(5): 310.

[25]

Ryu H. W., Song H. H., Shin I. S., Cho B. O., Jeong S. H., Kim D. Y., Ahn K. S., Oh S. R. J. Funct. Foods, 2015, 17: 774.

[26]

Liu J., Jin D. Z., Xiao L., Zhu X. Z. Brain Res., 2006, 1089(1): 162.

[27]

Liu D. Z., Xie K. Q., Ji X. Q., Yang Y., Jiang C. L., Zhu X. Z. Brit. J. Pharmacol., 2005, 146(4): 604.

[28]

Yi Y. N., Cheng X. M., Liu L. A., Hu G. Y., Cai G. X., Deng Y. D., Huang K. L., Wang C. H. Chem. Res. Chinese Universities, 2011, 27(5): 756.

[29]

Yang L. W., Wu D. H., Tang X., Peng W., Wang X. R., Ma Y., Su W. W. J. Chromatogr. A, 2005, 1070(1): 35.

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