A rapid identification of authenticity and specifications of Chinese medicine Fritillariae Cirrhosae Bulbus based on E-eye technology

LIU Rui-xin1,2,3,4 HAO Xiao-jia1 ZHANG Hui-jie1 ZHANG Lu2,3,4 GUI Xin-jing2,3,4 LIN Zhao-zhou5,6 LUO Chong-nian5,6 TIAN Liang-yu1 WANG Yan-li1 FENG Wen-hao1 YAO Jing2,3,4 LI Xue-lin1,2,3,4

(1.Henan University of Chinese Medicine, Zhengzhou, Henan Province, China 450008)
(2.Department of Pharmacy, the First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, Henan Province, China 450000)
(3.Research Center for Modern Engineering for Clinical Application of Chinese Medicine Decoction Pieces in Henan Province, Zhengzhou, Henan Province, China 450000)
(4.Co-construction Collaborative Innovation Center for Chinese Medicine and Respiratory Diseases Co-constructed by Province & Ministry, Henan University of Chinese Medicine, Zhengzhou, Henan Province, China 450000)
(5.Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China 100010)
(6.Beijing Institute of Traditional Chinese Medicine, Beijing, China 100035)
【Knowledge Link】leave-one-out cross-validation

【Abstract】The quality of TCM decoction pieces is correlated with clinical efficacy and drug safety, and plays a great role in promoting the development of TCM. However, the existing traditional artificial identification and modern instrument detection have both advantages and disadvantages in terms of accuracy and timeliness. Therefore, how to quickly and accurately identify the quality of TCM decoction pieces has become a high-profile issue. The purpose of this paper is to explore the feasibility of rapid identification of TCM quality by electronic-eye technology. A total of 80 batches of samples of Fritillariae Cirrhosae Bulbus were collected and tested by traditional empirical identification (M1) and modern pharmacopeia (M2). The optical data were collected from electronic eyes, and the chemometric method was used to establish suitable discrimination models (M3). Four authenticity and commodity specification models, namely discriminant analysis (DA), least-squares support-vector machines (LS-SVM), partial least squares discriminant analysis (PLS-DA), principal components analysis identification analysis (PCA-DA), were established separately. The accuracy of the authenticity identification models was 82.5%, 90.0%, 96.2%, and 93.8%, while that of the commodity specification identification models was 89.3%, 96.0%, 90.7%, and 97.3%, respectively. The models were well judged. The authenticity identification was based on the final identification model of PLS-DA, and the commodity specification was based on the final identification model of PCA-DA. There was no significant difference in accuracy between them and M1, and the time of determination was much shorter than M2 (P < 0.01). Therefore, electronic-eye technology could be used for the rapid identification of the quality of Fritillariae Cirrhosae Bulbus.

【Keywords】 electronic-eye; Fritillariae Cirrhosae Bulbus; quality identification; genuine/false; commodity specification; identification model;

【DOI】

【Funds】 General Project of National Natural Science Foundation of China (81774452, 81773892) Special Scientific Research Project of Traditional Chinese Medicine in Henan Province (2018ZY2131) Special Scientific Research Project of Traditional Chinese Medicine Clinical Research Base in Henan Province (2018JDZX087) Top-notch Talent Training Project of Traditional Chinese Medicine in Henan Province (2019ZYBJ07)

Download this article

    References

    [1] CAO J L, LI X L, MENG F, et al. Expert consensus on clinical application of Chinese herbal medicine decoction pieces (First Edition) [J]. China Journal of Chinese Materia Medica, 2020, 45 (13): 3238 (in Chinese).

    [2] LIU Y, ZHAO A Y, NI F Y, et al. Evaluation and analysis of high-quality products of Liuwei Dihuang Pills [J]. China Journal of Chinese Materia Medica, 2020, 45 (5): 1194 (in Chinese).

    [3] LI P, XU J G, JI D, et al. Correlation between appearance characteristics and intrinsic quality of Gastrodiae Rhizoma [J]. China Journal of Chinese Materia Medica, 2019, 44 (20): 4460 (in Chinese).

    [4] YANG R, LI W D, MA Y S, et al. The molecular identification of licorice species and the quality evaluation of licorice slices [J]. Acta Pharmaceutica Sinica, 2017, 52 (2): 318 (in Chinese).

    [5] ZHAI Y H, YU G Q, YANG Y M, et al. Physical and chemical identification on distinguishing Fritillariae ussuriensisBulbus from Fritillariae cirrhosa Bulbus [J]. West China Journal of Pharmaceutical Sciences, 2017, 32 (6): 633 (in Chinese).

    [6] YU G Q, WANG L L, WANG L L, et al. 贝母类药材的TLC鉴别 [J]. West China Journal of Pharmaceutical Sciences, 2016, 31 (4): 439 (in Chinese).

    [7] LUO D L, HUANG L J, HUANG L. Application of real-time fluorescent quantitative PCR in the Identification of Fritillariae Cirrhosae Bulbus [J]. China Pharmacist, 2016, 19 (6): 1068 (in Chinese).

    [8] WU X L, WANG Y, ZHAO X P. Screening and identification of DPP-4 inhibitors from Xiaokean formula by a fluorescent probe [J]. China Journal of Chinese Materia Medica, 2016, 41 (7): 1241 (in Chinese).

    [9] ZHANG X D, CHEN L, BAI Y, et al. Identification of crude products, counterfeit products and processed products of calamine by near infrared spectroscopy, principal component analysis and cluster analysis [J]. Chinese Journal of Experimental Traditional Medical Formulae, 2018, 24 (12): 1 (in Chinese).

    [10] WANG Y. 基于红外光谱与化学计量学对中药的鉴定方法研究 [D]. Beijing: Beijing University of Chinese Medicine, 2018 (in Chinese).

    [11] CHEN Q L. Determination of saponins in Pien Tze Huang by near infrared spectroscopy [J]. China Journal of Chinese Materia Medica, 2019, 44 (8): 1596 (in Chinese).

    [12] YU Y X, LI L, WANG Y Z. Discrimination of different species in Swertia using FTIR combined with chemometrics [J]. Chinese Journal of Experimental Traditional Medical Formulae, 2019, 25 (20): 114 (in Chinese).

    [13] MO Y J, WANG Y, ZHAI Q, et al. HPLC fingerprint of famous traditional formula Sanpian Decoction and quality value transmitting of Chuanxiong Rhizoma [J]. China Journal of Chinese Materia Medica, 2020, 45 (3): 572 (in Chinese).

    [14] QIAO F X, CAI H, TU P F, et al. Establishment and application of HPLC-QAMS for quality evaluation of Chuanxiong Rhizoma [J]. Acta Pharmaceutica Sinica, 2015, 50 (6): 749 (in Chinese).

    [15] LIU Z X, XU J, SUN W, et al. Application of DNA metabarcoding in species identification of Chinese herbal medicines [J]. China Journal of Chinese Materia Medica, 2019, 44 (1): 1 (in Chinese).

    [16] LU H S, LI T, JIANG D, et al. Identification and evaluation of Citrus grandis based on DNA barcode, UPLC and chromaticity method [J]. China Journal of Chinese Materia Medica, 2019, 44 (20): 4419 (in Chinese).

    [17] MA W Y, XIE Y Y, WANG Y M, et al. Emerging application and reflections of cell membrane chromatography in the quality evaluation of traditional Chinese medicine [J]. Acta Pharmaceutica Sinica, 2017, 52 (12): 1827 (in Chinese).

    [18] SUN L Y, LI Y N, CHEN S X, et al. Application of polymerase chain reaction-restriction fragment length polymorphism analysis in identification of Fritillariae Cirrhosae Bulbus [J]. Chinese Pharmaceutical Journal, 2018, 53 (23): 1992 (in Chinese).

    [19] WANG B, ZHOU Y X, TAN G, et al. Identification of adulteration in Fritillariae Cirrhosae Bulbus using multiplex ligation-dependent probe amplification technology [J]. Chinese Journal of Pharmaceutical Analysis, 2018, 38 (12): 2104 (in Chinese).

    [20] YAN H X, TAN C, DU X W, et al. Technical essentials for molecular biological method on identification of Fritillaria cirrhosa and its decoction pieces [J]. China Modern Medcine, 2017, 24 (6): 92 (in Chinese).

    [21] CHAI C C, MAO M, YUAN J F, et al. Correlation between color of Scutellariae Radix pieces and content of five flavonoids after softening and cutting by different methods [J]. China Journal of Chinese Materia Medica, 2019, 44 (20): 4467 (in Chinese).

    [22] LIU D P, WANG Y, WANG G Y, et al. Correlation analysis of color change and Maillard reaction during processing of Gardeniae Fructus Praeparatus [J]. China Journal of Chinese Materia Medica, 2020, 45 (10): 2382 (in Chinese).

    [23] XIU Y, LI Z, HOU X L, et al. Correlation between effective components content and color values of Gentianae Radix et Rhizoma based on color difference principle [J]. Chinese Journal of Experimental Traditional Medical Formulae, 2019, 25 (13): 151 (in Chinese).

    [24] WU C, XU L, MA Y C, et al. Correlation between color and contents of water and 5-hydroxymethylfurfural in Ginseng Radix et Rhizoma Rubra [J]. Chinese Journal of Experimental Traditional Medical Formulae, 2019, 25 (20): 136 (in Chinese).

    [25] GIORGIA O, ROSALBA C, GIORGIA F, et al. Data fusion of electronic eye and electronic tongue signals to monitor grape ripening [J]. Talanta, 2019, 195: 181.

    [26] KUMAR S B, ASHA M R, PRAKASH M. Quality mapping and positioning of Sev--a deep fat fried snack [J]. Int J Food Prop, 2014, 18 (11): 2433.

    [27] LUZURIAGA D A, BALABAN M O, YERALAN S. Analysis of visual quality attributes of white shrimp by machine vision [J]. J Sci Food AGR, 2010, 62 (1): 113.

    [28] WALLAT G K, LUZURIAGA D A, BALABAN M O, et al. Analysis of skin color development in live goldfish using a color machine vision system [J]. N AM J Aquacult, 2002, 64 (1): 79.

    [29] AABID S, JOSHUA K, PEDRO C L, et al. Automated image analysis for high-content screening and analysis [J]. J Biomol Screen, 2010, 15 (7): 726.

    [30] CRUZ D M, CRISTINE K A, BOSSO T J, et al. High content screening of a kinase-focused library reveals compounds broadly-active against dengue viruses [J]. Plos Neglect Trop D, 2013, 7 (2): 2073.

    [31] SANDADI S, PANDEY P, TURTON R. In situ, near real-time acquisition of particle motion in rotating pan coating equipment using imaging techniques [J]. Chem Eng Sci, 2004, 59 (24): 5807.

    [32] KETTERHAGN W R. Modeling the motion and orientation of various pharmaceutical tablet shapes in a film coating pan using DEM [J]. Int J Pharm, 2011, 409 (1/2): 137.

    [33] ZHANG X, WU H W, YU X K, et al. Quality evaluation of Andrographis Herba based on electronic-eye technique [J]. Chinese Journal of Experimental Traditional Medical Formulae, 2019, 25 (1): 189 (in Chinese).

    [34] Chinese Pharmacopoeia Commission. Chinese Pharmacopoeia, Volume I [S]. Beijing: China Medical Science Press, 2015 (in Chinese).

    [35] Shennong’s Classic of Materia Medica [M]. Tianjin: Tianjin Ancient Books Publishing House, 2009: 303 (in Chinese).

    [36] LI Z Y, DUAN Y H, QIN X M, et al. Study of difference in quality of traditional Chinese medicines [J]. Acta Pharmaceutica Sinica, 2017, 52 (12): 1820 (in Chinese).

    [37] LIU R X, CHEN P J, LI X L, et al. Artificial intelligence sense technology: new technology in pharmaceutical sciences [J]. Chinese Journal of Pharmaceutical Analysis, 2017, 37 (4): 559 (in Chinese).

    [38] YI Y W, CHEN G, BANG Y Q, et al. Sensory quality evaluation model of fermented millet pepper based on intelligent sensory [J]. Food & Machinery, 2018, 34 (9): 54 (in Chinese).

    [39] LEI Y H, LI H J, LI P. HPLC-ELSD specific chromatograms of alkaloid components in Fritillariae cirrhosae Bulbus [J]. Chinese Traditional Patent Medicine, 2014, 36 (7): 1477 (in Chinese).

    [40] WANG C Y, HE Z X, WU Y L. Method study of determination on total alkaloid content in different commercial specifications of Fritillaria Cirrhosa [J]. China Pharmaceuticals, 2013, 22 (15): 31 (in Chinese).

    [41] XU M F, WU Z S, LIU X N, et al. Quality evaluation method for Chinese medicine based on color grading [J]. China Journal of Chinese Materia Medica, 2016, 41 (2): 177 (in Chinese).

    [42] Gong J T, Zhao L Y, RUDOLF B, et al. “辨状论质”看中药材苦杏仁走油 [J]. China Journal of Chinese Materia Medica, 2016, 41 (23): 4375 (in Chinese).

    [43] ZHANG C, LI L, LIU Y, et al. Transformation of production mode and innovation of production technology of decoction pieces of Chinese crude drugs—feasibility study on intelligent production of decoction pieces of Chinese crude drugs [J]. China Journal of Chinese Materia Medica, 2018, 43 (21): 4352 (in Chinese).

    [44] DUAN J F, XIAO Y, LIU Y, et al. Optimization of steaming time of Cornus Officinalis by QAMS combined with electronic-eye and electronic-tongue techniques [J]. Chinese Traditional and Herbal Drugs, 2017, 48 (6): 1108 (in Chinese).

    [45] SHI Y, GONG F, WANG M, et al. A deep feature mining method of electronic nose sensor data for identifying beer olfactory information [J]. J Food Eng, 2019, 263: 437.

    [46] WU W Q, MAO Y N, LI H, et al. Identification of honeysuckle powder quality by Heracles Ⅱ ultra-fast gas phase electronic nose [J]. China Journal of Chinese Materia Medica, 2019, 44 (23): 5129 (in Chinese).

    [47] GONG J T, WANG J Y, LI L, et al. Identification of Curcuma herbs using XGBoost algorithm in electronic nose odor fingerprint [J]. China Journal of Chinese Materia Medica, 2019, 44 (24): 5375 (in Chinese).

    [48] Gong J T, Zhao L Y, Xu D, et al. Discrimination of Armeniacae Semen Amarum from different processed products and various rancidness degrees by electronic nose and support vector machine [J]. China Journal of Chinese Materia Medica, 2020, 45 (10): 2389 (in Chinese).

    [49] ARRIETA A A, ARRIETA P L, MENDOZA J M. Analysis of coffee adulterated with roasted corn and roasted soybean using voltammetric electronic tongue [J]. Acta Sci Pol tech, 2019, 18 (1): 35.

    [50] LIU F, XIE D S, LIU H M, et al. 电子舌技术鉴别川贝母粉及其掺伪品 [J]. Chinese Traditional Patent Medicine, 2017, 39 (9): 1977 (in Chinese).

    [51] LI X L, ZHANG Y, CHEN P J, et al. Study on superposition law of drug bitterness based on tongue taste evaluation and electronic tongue evaluation [J]. China Journal of Chinese Materia Medica, 2019, 44 (23): 5134 (in Chinese).

    [52] HONG M, SHI Y, SONGLIN F, et al. Mining feature of data fusion in the classification of beer flavor information using E-tongue and E-nose [J]. Sensors, 2017, 17 (7): 1656.

    [53] YANG S L. 基于智能感官分析技术的贝母及黄连饮片鉴别研究 [D]. Chengdu: Chengdu University of TCM, 2015 (in Chinese).

    [54] LAN Q K, ZHAO X, CHEN R, et al. Determination of bulbus of Fririllaria and processed products of Coptidis Rhizoma by using intelligent sensory technologies [J]. Chinese Journal of Pharmaceutical Analysis, 2019, 39 (3): 551 (in Chinese).

This Article

ISSN:1001-5302

CN: 11-2272/R

Vol 45, No. 14, Pages 3441-3451

July 2020

Downloads:0

Share
Article Outline

Knowledge

Abstract

  • 1 Materials
  • 2 Methods and results
  • 3 Discussion
  • 4 Conclusion
  • References