Abstract��OBJECTIVE To analyze and study the characteristic variables of wavelength in near-infrared spectroscopy of artificial cow-bezoar. METHODS A method of near-infrared spectroscopy coupled with competitive adaptive reweighted sampling(CARS) was performed in characteristic variables of wavelength screening for the qualitative and quantitative researches, respectively. RESULTS Some characteristic variables of wavelength, 0.48%-4.44% of all variables of wavelength, were screened out by CARS for different models. Not only the number of variables for building models decreased significantly, but also the index parameters for evaluating model became better. CONCLUSION This method is suitable for quality evaluation and quality control for artificial cow-bezoar.
CAO S, XIA J, YANG X H, et al. Optimization of determination of total bilirubin in three kinds of Bovis Calculus and Angongniuhuang pills[J]. Chin J Pharm Anal(ҩ�������־),2014,34(2):329-334.
[3]
XU L T, DING J H, SUN T J, et al. Determination of bilirubin in rengongniuhuangand its preparation[J]. Her Med(ҽҩ����), 2004, 23(1):49-50.
[4]
CHEN J, GAN G P, HE Z A, et al. Content analysis of bilirubin in niuhuang compound suppository by HPLC[J]. J Chin Med Master(��ҩ��), 2004, 27(10):772-774.
[5]
YE B B, PAN L, WANG D, et al. Simultaneous TLC-scanning determination of cholic acid and hyodeoxycholic acid in artificial Calculus Bovis[J]. Chin J Pharm Anal(ҩ�������־), 2010, 30(4):706-709.
[6]
WANG W Y, XIA J, JI S. Study on the determination of the artificial bezoar bezoarin NiuhuangBaolong tablet[J]. Chin Tradit Pat Med (�г�ҩ),2010, 32(3):436-439.
[7]
XUE C S, LI P. Improvement of colorimetric method for cholic acid in artificial bezoar[J]. Chin Pharm Aff(�й�ҩ��), 2000, 14(1):43-44.
[8]
YAN S K, WU Y W, LIU R H, et al. Comparative study on major bioactive components in natural, artificial and in-vitro cultured Calculus Bovis[J]. Chem Pharm Bull,2007,55(1):128-132.
[9]
XIONG J, ZHENG T J,SHI Y,et al. Study on simultaneous determination of major bile acids from artificial bezoar and metronidazole capsules by HPLC-ELSD[J]. Chin J Pharm Anal(ҩ�������־), 2015, 35(6):1067-1071.
[10]
KONG W, WANG J, ZANG Q, et al. Fingerprint-efficacy of artificial calculus bovis in quality control of Chinese materiamedica[J]. Food Chem, 2011, 127:1342-1347.
[11]
SHI Y, XIONG J, SUN D M, et al. Simultaneous quantification of the major bile acids in Artificial Calculus bovis by high-performance liquid chromatography with precolumn derivatization and its application in quality control[J]. J Sep Sci, 2015,38(16):2753-2762.
[12]
YAO L W, SHI Y, SUN D M, et al.The analysis of multivariate image and chemometrics in TLC fingerprinting of artificial cow-bezoar[J]. China J Chin Mater Med(�й���ҩ��־), 2017, 42(11):2117-2122.
[13]
QIAO X,YE M,PAN D L, et al. Differentiation of various traditional Chinese medicines derived from animal bile and gallstone: simultaneous determination of bile acids by liquid chromatography coupled with triple quadrupole mass spectrometry [J]. J Chromatogr A, 2011, 1218:107-117.
[14]
LIU Y Y, SHEN J T, WAN W B, et al. Online control of the mixing uniformity of Ginkgo Leaf Dispersible Tablets mixing online control by near-infrared spectroscopy[J]. Chin Pharm J(�й�ҩѧ��־), 2014,49(6):505-508.
[15]
QIU S J, LUO X J, ZHANG G S, et al. Non-destructive prediction of tablet hardness by near infrared diffuse reflection spectroscopy[J]. Chin Pharm J(�й�ҩѧ��־), 2016,51(11):904-909.
[16]
PENG Y F, SHI X Y, LI Y, et al. Optimization of near infrared variable selection method based on multivariate detection limit [J]. World Sci Technol Mod Tradit Chin Med Mater Med(�����ѧ����-��ҽҩ�ִ���), 2014,16(5):960-965.
[17]
DU C Z, ZHAO A B, WU Z S, et al. Online control of chlorogenic acid in Lonicerae Japonicae Flos by near infrared spectroscopy combined with different variable selections[J]. Chin Tradit Herb Drugs(�в�ҩ), 2017,48(16):3317-3321.
[18]
LI H D, LIANG Y Z, XU Q S, et al. Key wavelengths screening using competitive adaptive reweighted sampling method for multivariate calibration[J]. Anal Chim Acta, 2009, 648(1):77-84.
[19]
WU D, SUN D W. Potential of time series-hyperspectral imaging(TS-HSI) for non-invasive determination of microbial spoilage of salmon flesh[J]. Talanta, 2013, 111(13):39-46.
[20]
ZHANG J J. Research of discrimination maturity of apricots based on hyperspectral imaging technique[D]. Taigu:Shanxi Agric Univ(ɽ��ũҵ��ѧ),2015.
[21]
ZHANG X H. Discrimination on maturity of plums based on hyperspectral imaging technology [D]. Taigu:Shanxi Agric Univ(ɽ��ũҵ��ѧ),2016.
[22]
WANG H L, YANG G G, ZHANG Y, et al. Detection of fungal disease on tomato leaves with competitive adaptive reweighted sampling and correlation analysis methods[J]. Spectrosc Spectral Anali(����ѧ�������),2017,37(7):2115-2119.