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蜂蜜中乐果农药残留的表面增强拉曼光谱定量分析
引用本文:孙旭东,董小玲. 蜂蜜中乐果农药残留的表面增强拉曼光谱定量分析[J]. 光谱学与光谱分析, 2015, 35(6): 1572-1576. DOI: 10.3964/j.issn.1000-0593(2015)06-1572-05
作者姓名:孙旭东  董小玲
作者单位:1. 华东交通大学机电工程学院, 江西 南昌 330013
2. 华东交通大学外国语学院, 江西 南昌 330013
基金项目:国家自然科学基金项目,江西省教育厅青年基金项目,载运工具与装备教育部重点实验室项目资助
摘    要:应用表面增强拉曼光谱(surface-enhanced Raman spectroscopy, SERS)技术,结合线性回归算法,开展蜂蜜乐果中农药残留快速定量分析方法研究。含乐果农药残留的益母草蜂蜜样品30个作为被测对象,划分成建模集(20个)和预测集(10个)。采用具有规则倒四角锥体结构的Klarite基底作为增强基底,提高特征拉曼位移峰的相对强度。通过含乐果农药残留蜂蜜样品的SERS光谱与乐果标准品的常规拉曼光谱间的对比分析,找到了蜂蜜中乐果农药残留对应的四个特征拉曼位移峰867,1 065,1 317和1 453 cm-1。采用线性回归方法,建立了蜂蜜中乐果农药残留对应的四个特征拉曼位移峰强与乐果浓度间的线性回归模型。10个未参与建模的预测集样品,评价了模型的预测能力。经比较,采用867 cm-1处特征拉曼位移峰强建立的线性回归模型预测结果最优,模型预测相关系数为0.984,预测均方根误差为0.663 ppm。检测限达到2 ppm,接近我国农药残留最大限量标准的检测限。实验结果表明采用表面增强拉曼光谱技术结合线性回归算法实现蜂蜜中乐果农药残留的快速定量分析是可行的。可为其他农产品的农药残留快速定量分析提供参考依据。

关 键 词:光谱学  拉曼  表面增强拉曼  蜂蜜  农药残留   
收稿时间:2014-04-30

Quantitative Analysis of Dimethoate Pesticide Residues in Honey by Surface-Enhanced Raman Spectroscopy
SUN Xu-dong,DONG Xiao-ling. Quantitative Analysis of Dimethoate Pesticide Residues in Honey by Surface-Enhanced Raman Spectroscopy[J]. Spectroscopy and Spectral Analysis, 2015, 35(6): 1572-1576. DOI: 10.3964/j.issn.1000-0593(2015)06-1572-05
Authors:SUN Xu-dong  DONG Xiao-ling
Affiliation:1. School of Mechatronics Engineering, East China Jiaotong University, Nanchang 330013, China2. School of Foreign Language, East China Jiaotong University, Nanchang 330013, China
Abstract:The feasibility of a combination method of surface-enhanced Raman spectroscopy (SERS) technology and linear regression algorithm was investigated for rapid quantitative analysis of pesticide residues in honey. The total of 30 samples was applied in the experiment with dimethoate pesticide residues range from 1 ppm to 10 ppm. The samples were divided into calibration set (20) and prediction set (10). The substrate of Klarite with an inverted pyramidal structure was adopted for improvement of the relative intensity of the majority of Raman shift peaks. The comparative analysis was carried out between SERS spectra of dimethoate pesticide residues in honey samples and conventional Raman spectra of dimethoate standard sample. And four characteristic Raman shift peaks at the wavenumbers of 867, 1 065, 1 317 and 1 453 cm-1 were found, which were related with the vibrational information of dimethoate molecule. The relationship was developed by linear regression algorithm between the intensity of Raman shift and the concentration of dimethoate pesticide residues. The 10 new samples in the prediction set were applied to evaluate the performance of the models. By comparison, the optimal model was obtained with the characteristic Raman shift peak of 867 cm-1. The higher correlation coefficient of prediction of 0.984 and lower root mean square error of prediction of 0.663 ppm were obtained. The detection limit of this method was 2 ppm, which was close to the maximum levels of pesticide residue detection limits. Experimental results showed that it was feasible to rapidly analyze quantitative of pesticide residues in honey with the combination method of SERS technology and linear regression algorithm. Compared with the conventional method coupled with the suitable pretreatment, the combination method of SERS technology and linear regression method could analyze the dimethoate pesticide residues in honey, and it also provided an optional method for rapid quantitative analysis pesticide residues in other agricultural products.
Keywords:Spectroscopy  Raman spectroscopy  Surface-enhanced  Honey  Pesticide
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