高光谱结合人工神经网络鉴别不同来源的丹参饮片  

Identification of Salvia Miltiorrhiza Radix et Rhizoma from Different Origins by Hyperspectrum with Artificial Neural Network

作　　者：孙成玉 焦龙[1] 闫春华 王彩玲[2] 王薇[3] 张晟瑞[4] 王芹[4] SUN Chengyu;JIAO Long;YAN Chunhua;WANG Cailing;WANG Wei;ZHANG Shengrui;WANG Qin(College of Chemistry and Chemical Engineering,Xi′an Shiyou University,Xi′an 710065,China;College of Computer Science,Xi′an Shiyou University,Xi′an 710065,China;College of Pharmacy,Shaanxi University of Chinese Medicine,Xianyang 712046,China;School of Chemistry and Environment Science,Shaanxi University of Technology,Hanzhong 723000,China)

机构地区：[1]西安石油大学化学化工学院,西安710065 [2]西安石油大学计算机学院,西安710065 [3]陕西中医药大学药学院,咸阳712046 [4]陕西理工大学化学与环境科学学院,汉中723000

出　　处：《理化检验（化学分册）》2024年第3期271-276,共6页Physical Testing and Chemical Analysis(Part B:Chemical Analysis)

基　　金：国家自然科学基金(21807068,21775118,22177066);陕西省自然科学基金(2020KJXX-030,2021KJXX-51);陕西省教育厅青年创新团队建设科研计划项目(21JP097);陕西省教育厅科研计划项目资助(2023-JC-QN-0169);陕西省自然科学基础研究计划资助项目(22JP064);全国大学生创新创业培训计划项目(S202010705040);西安石油大学研究生创新与实践能力培养项目(YCS21211036)。

摘　　要：提出了高光谱结合人工神经网络法(ANN)鉴别不同来源丹参饮片的方法。采集了9种不同来源丹参饮片的高光谱;分别采用最大最小归一化、均值中心化、标准正态变量变换、Savitzky-Golay平滑滤波、多元散射校正等5种光谱预处理方法,结合ANN建立了鉴别这些样品来源的分类模型。测试集验证结果表明,当隐含层节点数设置为17时,对光谱进行均值中心化预处理可建立最佳的ANN模型,分类准确率为98.77%。7种丹参样品判别结果的真正率、命中率和特异度均达到100.00%;其余2种丹参样品的真正率、命中率和特异度也不小于90.00%。A method for identification of Salvia Miltiorrhiza Radix et Rhizoma from different origins was propsed by hyperspectrum with artificial neural network(ANN).The hyperspectra of Salvia Miltiorrhiza Radix et Rhizoma samples from 9 different origins were collected.The classification model for identification of origins of these samples was developed by using ANN combined with 5 different spectral preprocessing methods(maximum and minimum normalization,mean centralization,standard normal transformation,Savitzky-Golay smooth derivative and multiple scattering correction).As shown by the results of test set,when the number of hidden layer nodes was set to 17,the best model was developed by the mean centered method combined with ANN,with a classification accuracy of 98.77%.The sensitivity,precision and specificity of discrimination results from 7 Salvia Miltiorrhiza Radix et Rhizoma samples had reached 100.00%,the other 2 Salvia Miltiorrhiza Radix et Rhizoma samples were not less than 90.00%.

关 键 词：高光谱 人工神经网络 定性分类 中药 丹参 

分 类 号：O657.3[理学—分析化学]