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不同生长期当归红外光谱的偏最小二乘分析
引用本文:李四海,潘新波,任真,顾志荣,王亚丽.不同生长期当归红外光谱的偏最小二乘分析[J].中国实验方剂学杂志,2013,19(12):132-135.
作者姓名:李四海  潘新波  任真  顾志荣  王亚丽
作者单位:甘肃中医学院当归研究所,兰州,730000
基金项目:国家自然科学基金项目(30960037);甘肃省发改委战略新兴产业和产业技术研究与开发专项项目
摘    要:目的:研究偏最小二乘(PLS)方法在不同生长期当归傅里叶变换红外光谱(FT-IR)分析中的应用.方法:使用正交信号校正及小波压缩(OSCW)对原始FT-IR信号进行预处理,然后对预处理后的光谱信号进行PLS分析,提取前2个主成分对3种不同生长期的当归进行聚类.结果:3种生长期的当归被正确地分为3类,聚类结果与当归的生长期密切相关,反映了不同生长期当归在主要化学成分含量上存在一定的差异.结论:对光谱信号进行正交信号校正及小波压缩处理能够有效降低光谱信号的噪声,有助于提高聚类性能.

关 键 词:当归  傅里叶变换红外光谱  正交信号校正  偏最小二乘
收稿时间:2013/1/15 0:00:00

PLS Analysis of FT-IR Spectrum of Angelica sinensis at Different Growth Stages
LI Si-hai,PAN Xin-bo,REN Zhen,GU Zhi-rong and WANG Ya-li.PLS Analysis of FT-IR Spectrum of Angelica sinensis at Different Growth Stages[J].China Journal of Experimental Traditional Medical Formulae,2013,19(12):132-135.
Authors:LI Si-hai  PAN Xin-bo  REN Zhen  GU Zhi-rong and WANG Ya-li
Institution:Gansu College of Traditional Chinese Medicine, Research Institute of Angelia Sinensis, Lanzhou 730000, China;Gansu College of Traditional Chinese Medicine, Research Institute of Angelia Sinensis, Lanzhou 730000, China;Gansu College of Traditional Chinese Medicine, Research Institute of Angelia Sinensis, Lanzhou 730000, China;Gansu College of Traditional Chinese Medicine, Research Institute of Angelia Sinensis, Lanzhou 730000, China;Gansu College of Traditional Chinese Medicine, Research Institute of Angelia Sinensis, Lanzhou 730000, China
Abstract:Objective: To study application of partial least squares in fourier transforn infrared spectroscopy(FT-IR) spectrum analysis for Angelica sinensis at different growth stages. Method: Pretreatment method of orthogonal signal correction and wavelet compression(OSCW) was used to reject uncorrelated variables in the original spectra before partial least squares(PLS) analysis. the first two principal components were employed to cluster samples of A. sinensis at different growth stages. Result: All samples are properly classified into three categories according to their growth stage, the results of clustering was closely related to their growing period, which reflect the differences in relative content of main chemical composition among the samples from various growing period. Conclusion: The proposed method that established with orthogonal signal correction plus wavelet compression can decrease noise of FT-IR spectrum and help to improve the clustering performance.
Keywords:Angelica sinensis  fourier transform infrared spectroscopy  orthogonal signal correction  partial least squares
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