Qualitative and Quantitative Analysis of Paris polyphylla var. yunnanensis in Different Harvest Times with Infrared Spectroscopy Combined with Chemometrics
WU Zhe1,2,3, ZHANG Ji1,2, JIN Hang1,2, WANG Yuan-zhong1,2*, ZHANG Jin-yu1,2*
1. Institute of Medicinal Plants, Yunnan Academy of Agricultural Sciences, Kunming 650200, China
2. Yunnan Technical Center for Quality of Chinese Materia Medica, Kunming 650200, China
3. College of Traditional Chinese Medicine, Yunnan University of Traditional Chinese Medicine, Kunming 650500, China
Abstract：In order to provide a scientific basis tor find out the best harvest time. Fourier transform infrared (FT-IR) spectroscopy combined with partial least squares discriminant analysis (PLS-DA) and partial least squares regression (PLSR) were used for the identification and evaluation of Paris polyphylla var. yunnanensis from different harvest times. Infrared spectra of 46 samples from different harvest times were collected. The original spectra were pretreated with automatic baseline correction, ordinate normalization, automatic smoothing and wavelet denosing prior to PLS-DA. The contents of polyphyllin Ⅰ, Ⅱ, Ⅵ and Ⅶ were determined with ultra performance liquid chromatography (UPLC). The PLSR model was established combining the spectral data with the reference data performed by UPLC data for evaluating the quality of polyphyllin Ⅰ, Ⅱ, Ⅵ and Ⅶ after the preprocessing of automatic baseline correction, ordinate normalization, automatic smoothing, first derivative and Orthogonal signal correction (OSC). Results showed that: (1) The main absorptions of the original spectra were in the ranges of 950~700, 1 200~950, 1 800~1 500 and 2 800~3 500 cm-1. (2) The PLS-DA score plot could accurately distinguish P. polyphylla var. yunnanensis from different harvest times. (3) According to the UPLC data, it was found that the total content of polyphyllin Ⅰ, Ⅱ, Ⅵ and Ⅶ got a fold increase, then elicited a decline, and finally showed a slow upward trend with the growth period. (4)There was no significant differences between the predicted value based on quantitative model and measured value with UPLC, and the effect of the model was good. FT-IR spectroscopy combined with chemometrics could clearly distinguish P. polyphylla var. yunnanensis from different harvest times and reach a fast prediction for the content of polyphyllin. Furthermore, it could provide a method for distinguishing and forecasting polyphyllin and a theoretical basis for best harvest time of P. polyphylla var. yunnanensis.
Key words：Infrared spectroscopy; Harvest times; Paris polyphylla Smith var. yunnanensis; Polyphyllin; PLS-DA; PLSR
吴 喆，张 霁，金 航，王元忠，张金渝. 红外光谱结合化学计量学对不同采收期滇重楼的定性定量分析[J]. 光谱学与光谱分析, 2017, 37(06): 1754-1758.
WU Zhe, ZHANG Ji, JIN Hang, WANG Yuan-zhong, ZHANG Jin-yu. Qualitative and Quantitative Analysis of Paris polyphylla var. yunnanensis in Different Harvest Times with Infrared Spectroscopy Combined with Chemometrics. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 37(06): 1754-1758.
[1] Cheng C, Liu J, Wang H, et al. Applied Spectroscopy Reviews, 2010, 45(3): 165.
[2] Li Y, Liu B, Geng S, et al. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2016, 157: 186.
[3] Liu D, Mei Q, Wan X, et al. Journal of Chromatographic Science, 2015，53(10)：1680.
[4] Chen N D, Chen N F, Li J, et al. Journal of Molecular Structure, 2015, 1101: 101.
[5] Lu Y, Huang J, Li Y, et al. Food Chemistry, 2015, 183: 91.
[6] Chinese Pharmacopoeia Commission(国家药典委员会). Pharmacopoeia of the People’s Republic of China(中华人民共和国药典), Part One(第一部). Beijing: China Medical Science Press(北京: 中国医药科技出版社), 2015. 260.
[7] Zhang J Y, Wang Y Z, Zhao Y L, et al. Journal of Asian Natural Products Research, 2011, 13(7): 670.
[8] FENG Li-li, ZHANG Lin, LI Hai-feng, et al(冯丽丽, 张 琳, 李海峰, 等). Chinese Pharmaceutical Journal(中国药学杂志), 2015, 50(8): 664.
[9] Li X, Chen Y, Lai Y, et al. Evid Based Complement Alternat Med., 2015, 2015: 218901.
[10] ZHAO Ting-zhou, WANG Bu-qiong, MA Qing, et al(赵庭周, 王卜琼, 马 青, 等). Chinese Wild Plant Resources(中国野生植物资源), 2014, 33(5): 61.
[11] CHEN Shi-lin, GUO Bao-lin, ZHANG Gui-jun(陈士林, 郭宝林, 张贵君). Chinese Pharmaceutical Journal(中国药学杂志), 2012, 37(8): 1043.
[12] Cebi N, Durak M Z, Toker O S, et al. Food Chemistry, 2016, 190: 1109.
[13] Botelho B G, Reis N, Oliveira L S, et al. Food Chemistry, 2015, 181: 31.
[14] Chavez P F, Sacre P Y, De Bleye C, et al. Talanta, 2015, 144: 1352.
[15] Feng Y, Lei D, Hu C. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2014, 125: 363.
[16] Zhao Y, Zhang J, Jin H, et al. Journal of AOAC International, 2015, 98(1): 22.
[17] Shao Q S, Zhang A, Ye W W, et al. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2014, 120: 499.
[18] Rohaeti E, Rafi M, Syafitri U D, et al. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2015, 137: 1244.
[19] Wang P, Zhang H, Yang H, et al. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2015, 137: 1403.
[20] YAN Qian(颜 茜). The Journal of Light Scattering(光散射学报), 2013, 25(1): 85.
[21] Chen J, Sun S, Ma F, et al. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2014, 128: 629.
[22] Hashim D M, Man Y B C, Norakasha R, et al. Food Chemistry, 2010, 118(3): 856.
[23] Rinnan , van den Berg F, Engelsen S B. Trends in Analytical Chemistry, 2009, 28(10): 1201.
[24] Wold S, Antti H, Lindgren F, et al. Chemometrics and Intelligent Laboratory Systems, 1998, 44(1): 175.
[25] Bassbasi M, De Luca M, Ioele G, et al. Journal of Food Composition and Analysis, 2014, 33(2): 210.
[26] Ciosek P, Brzózka Z, Wróblewski W, et al. Talanta, 2005, 67(3): 590.
[27] Zhao N, Wu Z, Zhang Q, et al. Scientific Reports, 2015, 5：11647.
[28] Shetty N, Gislum R. Field Crops Research, 2011, 120(1): 31.
[29] Pande R, Mishra H N. Food Chemistry, 2015, 172: 880.
[30] Jandric Z, Haughey S A, Frew R D, et al. Food Chemistry, 2015, 5: 11647.
[31] Xie L, Ye X, Liu D, et al. Food Chemistry, 2009, 114(3): 1135.
