表面增强拉曼光谱法快速检测脐橙果肉中三唑磷农药残留

发布时间：2018-03-26 16:52

本文选题：表面增强拉曼光谱　切入点：脐橙果肉　出处：《光谱学与光谱分析》2016年03期

【摘要】：采用表面增强拉曼光谱技术结合快速溶剂前处理方法检测脐橙果肉中三唑磷农药残留,应用化学计量学方法建立脐橙果肉中三唑磷农药残留的快速检测模型。以脐橙果肉提取液为基质,采用N-丙基乙二胺、C18和石墨化碳去除果肉中有机酸、色素等荧光物质,配制不同浓度的三唑磷农药溶液,应用不同预处理方法对光谱信号进行预处理,建立偏最小二乘模型。结果表明,以脐橙果肉提取液为基质的三唑磷溶液最低检测浓度低于0.5mg·L-1;归一化预处理后建立的模型预测性能最好,模型对预测集样本的均方根误差为1.38mg·L-1,相关系数为0.976 6,相对分析误差为(RPD)4.66。预测回收率为95.97%~103.18%,相对误差绝对值在5%以下,表明模型具有较好的预测效果。对4个未知浓度样本进行配对t检验,预测值与真实值无显著差异,说明所建立的方法准确可靠。
[Abstract]:The use of surface enhanced Raman spectroscopy combined with rapid solvent pretreatment method for the detection of three Triazophos pesticide residues in orange pulp, the application of chemometrics methods to establish rapid detection model of three Triazophos pesticide residues in orange pulp. Extract as substrate to orange pulp, using N- propyl ethylenediamine, C18 and graphitized carbon removal of organic acids in pulp, pigment other fluorescent substances, three Triazophos pesticide solution with different concentrations, the application of different pretreatment methods on the spectral signal preprocessing, the partial least squares model was established. The results showed that the extract is three to orange flesh Triazophos solution the lowest detectable concentration of substrate is lower than 0.5mg - L-1 model to predict the performance; establish the normalization after pretreatment of the best the root mean square error, model samples for prediction of 1.38mg - L-1, the correlation coefficient is 0.9766, the relative error analysis for 4.66. (RPD) to predict the recovery rate was 95.97%~103. 18%, the absolute value of relative error is below 5%, which indicates that the model has good prediction effect. Paired t test for 4 unknown concentration samples shows no significant difference between predicted value and real value, indicating that the established method is accurate and reliable.

【作者单位】：江西农业大学生物光电及应用重点实验室;江西出入境检验检疫局技术中心;江西农业大学农学院;
【基金】：赣鄱英才555工程人选计划(2012-62) 国家自然科学基金项目(31271612) 江西省学术带头人培养计划(20113BCB22001)资助
【分类号】：O657.37;TS255.7

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