蔷薇科植物的红外光谱分类研究  

Classification of Rosaceae Plants by Infrared Spectroscopy

作　　者：郑钧文 宋霄雪 甘玉佳 吴衷宇 杨忠钰 欧全宏[1] 时有明[2] 刘刚[1] Zheng Junwen;Song Xiaoxue;Gan Yujia;Wu Zhongyu;Yang Zhongyu;Ou Quanhong;Shi Youming;Liu Gang(School of Physics and Electronics,Information,Yunnan Normal University,Kunming 650500,Yunnan,China;School of Physics and Electronic Engineering,Qujing Normal University,Qujing 655011,Yunnan,China)

机构地区：[1]云南师范大学物理与电子信息学院,云南昆明650500 [2]曲靖师范学院物理与电子工程学院,云南曲靖655011

出　　处：《激光与光电子学进展》2024年第9期492-500,共9页Laser & Optoelectronics Progress

基　　金：国家自然科学基金(31760341);云南省教育厅基金(2022J0129);云南省高校科技创新团队支持计划。

摘　　要：不同蔷薇科植物种类资源信息的收集与明确其科、属间亲缘关系对蔷薇科植物资源的开发利用有重要意义。以不同种类蔷薇科植物的叶片、花瓣及雄蕊为材料,用傅里叶变换红外(FTIR)光谱结合主成分分析(PCA)、系统聚类分析(HCA)、簇类独立软模式法(SIMCA)判别模型对蔷薇科植物进行研究。结果表明,蔷薇科叶片、花瓣及雄蕊中均含有多糖、蛋白质、脂类、草酸钙、木质素等成分,花瓣和雄蕊中还含有酚类物质。不同种类叶片之间的FTIR光谱吸收特征相似,但在1660~1000 cm^(-1)范围内吸收峰强度存在明显差异,利用此范围进行PCA,前两个主成分可获得97%以上的累计方差贡献率,用HCA可将11种植物在亚科级别正确分类。结合SIMCA判别模型,对不同叶片、花瓣及雄蕊的蔷薇科植物进行分类,用全谱4000~400 cm^(-1)范围数据,正确分类率可达96.08%;用1800~800 cm^(-1)范围数据,正确分类率可达100%。研究表明,FTIR光谱结合统计分析方法及判别模型,可以将不同种类蔷薇科植物在亚科、属级别上正确分类。For the development and utilization of Rosaceae plant resources,it is of great significance to collect information on different Rosaceae plant species and clarify their family and generic relationships.In this study,leaves,petals,and stamens of different Rosaceae plant species are analyzed through Fourier transform infrared(FTIR)spectroscopy combined with principal component analysis(PCA),hierarchical cluster analysis(HCA),and soft independent modelling of class analogy(SIMCA).The results revealed that the leaves,petals,and stamens of Rosaceae contained polysaccharides,proteins,lipids,calcium oxalate,lignin,and other components,while the petals and stamens contained phenols in addition.The FTIR spectra of different types of leaves are found to be similar,but the absorption peak intensities in the range of 1660‒1000 cm^(-1) differed significantly.Upon using this range for PCA,the first two principal components could achieve more than 97%of the cumulative variance contribution rate.Using HCA,11 species of the plant could be correctly classified at the subfamily level.Combined with the SIMCA discriminant model,in the classification of Rosaceae plants with different leaves,petals,and stamens,the correct classification rate reaches 96.08%with the full spectral data in the range of 4000‒400 cm^(-1),and 100%accuracy can be achieved with the data in the range of 1800‒800 cm^(-1).The results reveal that FTIR spectroscopy combined with statistical analysis and discriminant modeling is a suitable method for accurately classifying different species of Rosaceae plants at subfamily and genus levels.

关 键 词：红外光谱 蔷薇科 化学计量学 主成分分析 系统聚类分析 簇类独立软模式法 

分 类 号：O657.33[理学—分析化学]