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表面增强喇曼光谱研究脐橙中亚胺硫磷农药残留

Quantitative study on phosmet residues in navel oranges based on surface enhanced Raman spectra

  • 摘要: 为了证实以团絮状银胶为基底的表面增强喇曼光谱(SERS)技术结合化学计量学方法能有效实现脐橙中农药残留检测,采用德国布鲁克公司的共焦显微喇曼光谱仪,对脐橙中的亚胺硫磷农药残留的快速无损检测进行了研究。通过留一交互验证法得出农药检出限为4.113mg/L,并对SERS光谱进行7种方法的预处理。结果表明,先基线校正后卷积平滑预处理的建模预测效果最好;结合偏最小二乘法建模,预测集的相关系数和预测均方根误差分别为0.904和4.890mg/L,校正集的相关系数和预测均方根误差分别为0.919和3.990mg/L。结果证明了SERS定量分析的科学性和可行性,这对国内水果的生产和出口水果的农药残留检测有一定的参考作用。

     

    Abstract: In order to confirm that surface enhanced Raman spectroscopy (SERS) with flocculent colloid as substrate, combined with chemometric methods, can effectively detect pesticide residues in oranges, rapid and nondestructive detection of phosmet pesticide residues in navel oranges was studied with the help of confocal laser Raman spectrometer of Germany Bruker Optik GmbH. Detection limit of 4.113mg/L was concluded by cross validation method, and 7 methods of pretreatment of SERS spectra were carried out. After comparison, pretreatment method is the best with baseline correction at first, and then convolution smoothing, combined with partial least squares modeling. Correlation coefficient of prediction set is 0.904 and root mean square error of prediction set is 4.890mg/L. Correlation coefficient of correction set is 0.919 and root mean square error of correction set is 3.990mg/L. The results prove that the scientificity and feasibility of quantitative analysis of SERS. The study has certain reference in pesticide residue detection of export fruit and industrial production of domestic fruit.

     

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