摘要
采用高光谱结合支持向量机方法(SVM)建立了不同产地丹参药材的鉴别方法。采集了6种不同产地丹参药材的高光谱;之后,分别使用均值中心化和Savitzky-Golay平滑滤波2种光谱预处理方法,结合SVM建立丹参产地鉴别模型;Savitzky-Golay平滑滤波方法结合SVM分类效果最佳,测试集分类准确率为97.50%,同时具有更高的真正率、命中率、和特异度。研究结果表明,建立的高光谱技术结合支持向量机方法步骤简便、准确、可靠,是一种很有前景的丹参药材分析鉴别方法。
Hyperspectrum combined with support vector machine(SVM)method was established to identify Salvia miltiorrhiza samples from different geographical regions.In the experiment,the hyperspectra of 6 kinds of Salvia miltiorrhiza samples from different regions were collected.Then a discriminant model was established by SVM method combined with 2 different spectral preprocessing methods(Mean centralization and Savitzky-Golay smooth derivative).The Savitzky-Golay smooth derivative combined with SVM had the best discrimination effect,and the test set classification accuracy was 97.50%.The overall results showed that hyperspectral technique combined with support vector machine method was a promising method for the analysis and identification of Salvia miltiorrhiza.
作者
孙成玉
焦龙
Sun Cheng-yu;Jiao Long(College of Chemistry and Chemical Engineering,Xi'an Shiyou University,Xi'an,Shaanxi 710065,China)
出处
《福建分析测试》
CAS
2023年第2期11-15,共5页
Fujian Analysis & Testing
基金
西安石油大学研究生创新与实践能力培养项目(批准号:YCS21211036)资助。
关键词
高光谱
支持向量机
定性分类
中药
丹参
hyperspectrum
supportvectormachine
qualitativeclassification
traditionalChinesemedicine
Salvia miltiorrhiza
