密度泛函理论结合拉曼光谱法对大豆品种的分类鉴别

Classification and identification of soybean varieties by density functional theory combined with Raman spectroscopy

针对东北地区多个品种大豆的分类鉴别需求,本文采用理论计算与实验分析相结合的研究方法,开展对6个品种大豆的分类鉴别。油酸和亚油酸是大豆的重要构成成分,首先以密度泛函理论为基础,构建油酸和亚油酸分子空间结构,并利用B3LYP/6-31+G(d,p)基组优化并计算其理论拉曼光谱。再通过实验获取油酸、亚油酸分析纯和6个品种大豆的拉曼光谱,并将所得理论拉曼光谱与实验拉曼光谱做出比对,发现各品种大豆均在1281、1445、1662和2904 cm^(-1)处有较强拉曼峰。最后以此四个拉曼峰作为特征峰,运用主成分分析法(PCA)和线性判别分析法(LDA)对不同品种大豆做可视化分类,分类正确率达到90%。研究结果表明,密度泛函理论结合拉曼光谱法能够开展对大豆品种的有效分类,对智慧农业的发展提供了一定借鉴意义。

According to the needs of classification and identification of many varieties of soybean in Northeast China,this paper uses the research method of combining theoretical calculation and experimental analysis to carry out the classification and identification of 6 varieties of soybean.Oleic acid and linoleic acid are important components of soybean.Firstly,based on density functional theory,the molecular spatial structures of oleic acid and linoleic acid were constructed,and the theoretical Raman spectra were optimized and calculated by B3LYP/6-31+G(d,p)basis set.Then,the Raman spectra of oleic acid,linoleic acid analytical purity and six varieties of soybean were obtained by experiment,and the theoretical Raman spectra were compared with the experimental Raman spectra.It was found that all varieties of soybean had strong Raman peaks at 1281,1445,1662 and 2904 cm^(-1).Finally,taking the four Raman peaks as the characteristic peaks,the principal component analysis(PCA)and linear discriminant analysis(LDA)were used to visually classify different varieties of soybeans,and the classification accuracy reached 90%.The results show that density functional theory combined with Raman spectroscopy can effectively classify soybean varieties,which provides a certain reference for the development of intelligent agriculture.