基于红外光谱与聚类分析法的宁夏产地枸杞子品种鉴别研究

doi:10.3964/j.issn.1000-0593(2024)05-1386-06

Abstract
References
Related Citation (15)

Download: PDF (2083 KB)
Export: BibTeX | EndNote (RIS)

Abstract Lycium barbarum(Lycii Fructus, wolfberry) is a valuable traditional Chinese medicinal material for medicine and food. Ningxia Zhongning wolfberry cultivars have been introduced to Gansu, Xinjiang, Qinghai and other provinces. Due to long-term introduction and improvement, there are many varieties of Lycium barbarum, one of the important factors affecting the quality of Lycii Fructus. This study used Fourier transforms infrared spectroscopy (FTIR) to determine the collected Lycii Fructus of Ningqi No.1, No.4, No.5, No.7, No.0909 and No.10 from Zhongning, Ningxia. The range of the one-dimensional infrared spectrum and the second derivative spectrum was 4 000~650 cm^-1. After obtaining the spectrum, the infrared spectrum's similarity coefficient was calculated using the fingerprint region (1 800~650 cm^-1) with dense spectral bands. Then, the infrared fingerprints of different varieties of Lycii Fructus were classified and compared with SMICA cluster analysis. The results show that the one-dimensional infrared spectroscopy of different varieties of Lycium barbarum samples are relatively similar, with the location, peak height and peak shape of the peaks being relatively close. Their common absorption peaks are more numerous, and only the intensity, peak location and peak shape of the absorption peaks at around 3 282～3 288, 1 239～1 242 and 1 143～1 147 cm^-1 are different, indicating that the polysaccharides, glycosides, proteins, lipids, and The types and contents of polysaccharides, glycosides, proteins, lipids, flavonoids and other components in different varieties of Lycium barbarum varied. In the second-order derivative spectra, the absorption peaks of NingQi 1, 4 and 7 were not apparentat 2 880 cm^-1, and 0909 at 969 cm^-1. The similarity of different varieties of Lycii Fructus ranges from 0.9489 to 0.9928, indicating certain differences among different varieties. Ningqi 7 has the lowest average similarity coefficient of 0.9640, indicating that its component specificity is the highest. The similarity coefficient of No.0909 and Ningqi 10 is 0.992 8, the two varieties with the highest similarity. The cluster analysis was carried out using the Assure ID software with the absorption wave number of each medicinal material as a variable. The class spacing between Ningqi No.1 and other varieties was small, ranging from 2.17 to 2.97. The class spacing between No.0909 and other varieties was the largest, ranging from 2.97 to 8.06. In the clustering model, the recognition rate of different varieties of Lycii Fructus is 100%, only the rejection rate of Ningqi No.1 is 66%, which can easy to be confused with other varieties of Lycii Fructus, and the rejection rate of No.0909 is 100%, which is the easiest to distinguish. In the class model diagram, No.0909 and Ningqi No.5, No.0909 and Ningqi No.7 are separated in pairs, which can identify the samples of different varieties. The cluster analysis model was verified using known varieties of Lycii Fructus, and its recognition and rejection rates were the same as those of the cluster analysis model. The results of the one-dimensional infrared spectrum, second derivative spectrum, similarity, class spacing, recognition rate and rejection rate of different varieties of Lycii Fructus showed that Ningqi No.1 was the original variety of other varieties of Lycii Fructus, and No.0909 was significantly different from other varieties. Therefore, the combination of infrared spectrum and cluster analysis can quickly and nondestructively identify different varieties of Lycii Fructus, which has a certain guiding role in the breeding and production of Lycii Fructus in Ningxia.

Key words：Infrared spectroscopy; Cluster analysis; Lycium barbarum; Different varieties; Identification

Received: 2022-09-08 Accepted: 2023-09-22

ZTFLH:

R282

Corresponding Authors: AO Dong-mei, XU Chang-qing E-mail: admei302@163.com；cqxu@implad.ac.cn

Cite this article:

XU Rong,AO Dong-mei,XU Xin, et al. Study on the Identification Method of Lycium Barbarum Cultivars in Ningxia Based on Infrared Spectrum and Cluster Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(05): 1386-1391.

URL:

https://www.gpxygpfx.com/EN/10.3964/j.issn.1000-0593(2024)05-1386-06 OR https://www.gpxygpfx.com/EN/Y2024/V44/I05/1386

[1] 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). Beijing: China Medical Science and Technology Press(北京: 中国医药科技出版社), 2020. 260.
[2] SONG Yan-mei, ZHANG Qi-li, CUI Zhi-jia, et al(宋艳梅, 张启立, 崔治家, 等). West China J. Pharm. Sci.(华西药学杂志), 2022, 37(2): 206.
[3] ZENG Yong-chang, LIANG Shao-yu, JIANG Qian-qian, et al(曾永长, 梁少瑜, 姜倩倩, 等). Chinese Traditional Patent Medicine(中成药), 2022, 447(2): 2362.
[4] YU Jia-xiang, ZHANG Han-wen, QU Chao, et al(于嘉祥, 张瀚文, 曲超, 等). Modernization of Traditional Chinese Medicine and Materia Medica-World Science and Technology(世界科学技术-中医药现代化), 2021, 23(11): 3397.
[5] LI Qiu-jiang, FANG Xiao-min, WANG Yin-bin, et al(李秋江, 房晓敏, 王胤斌, 等). Chin J. Osteoporos(中国骨质疏松杂志), 2021, 27(12): 1757.
[6] WANG Yun, HU Xiao-nan(王云, 胡晓楠). Food Research and Development(食品研究与开发), 2020, 41(23): 56.
[7] CAO Xiu-peng, CHEN Xia, GUO Ya-tu, et al(曹秀朋, 陈霞, 郭雅图, 等). Rec. Adv. Ophthalmol.(眼科新进展), 2020, 40(6): 510.
[8] LIU Yao-jie, LIU Ying, LIU Dong, et al(刘垚杰, 刘莹, 刘东, 等). Food Research and Development(食品研究与开发), 2021, 42(1): 60.
[9] WU Dong-li, QIAO Xin-hua, HAN Wen-sheng, et al(伍东立, 乔新华, 韩文生, 等). Progressin Biochemistryand Biophysics(生物化学与生物物理进展), 2023, 50(8): 1926.
[10] SUN Hong-liang(孙红亮). Journal of Shanxi Agricultural University（Natural Science Edition）[山西农业大学学报(自然科学版)], 2021, 41(2): 99.
[11] SUN Hong-liang(孙红亮). Molecular Plant Breeding(分子植物育种), 2022, 20(18): 6177.
[12] LIU Ling-ling, WANG You-you, YANG Jian, et al(刘玲玲, 王游游, 杨健, 等). China Journal of Chinese Meteria Medica(中国中药杂志), 2023, 48(16): 4328.
[13] ZHOU Feng-ran, HAN Qiao, ZHANG Ti-qiang, et al(周枫然, 韩桥, 张体强, 等). Chem. Reagents(化学试剂), 2021, 43(8): 1001.