作　　者： (刘翠玲）; (邢瑞芯）; (孙晓荣）; (赵琦）;

机构地区： 北京工商大学计算机与信息工程学院、食品安全大数据技术北京市重点实验室,北京100048

出　　处： 《食品工业科技》 2017年第17期245-249,共5页

摘　　要： 本文针对菠菜农药残留量超标问题,建立了一种能够快速、无损地对菠菜表面农药残留量进行检测的方法。利用表面增强拉曼光谱技术(SERS,Surface Enhanced Raman Scattering)采集含农药(溴氰菊酯)和不含的两组菠菜样本的SERS光谱,结合一阶导加Norris求导法、Savitzky-Golay卷积求导法进行光谱预处理,使用判别分析法和距离匹配法建立定性分析模型,成功区分两组菠菜样本,模型预测准确率最高可达到100%;使用偏最小二乘法建立了菠菜表面溴氰菊酯残留量的多个定量分析模型,研究发现差谱模型效果最好,其校正集相关系数(Rc)和预测集相关系数(Rp)分别为0.9908,0.9552,校正均方根误差(RMSEC)和预测均方根误差(RMSEP)分别为0.0802,0.23。结果表明,运用SERS方法能够很好地实现菠菜表面溴氰菊酯残留量的无损定性和定量检测分析,且无需任何前处理,对其它农产品中农药残留量的快速、无损检测具有借鉴意义。 A method for rapid and nondestructive detection of pesticide residues on spinach surface by using surface enhanced raman scattering（SERS） was built in this paper.SERS of spinach samples with and without deltamethrin were pretreated with some methods such as first derivation, Norris derivation and Savitsky-Golay convolution derivation.Diseriminant analysis and distance match method were used to build qualitative model for determination of spinach samples with and without dehamethrin, and the highest accuracy rate of prediction was proved to be 100% .Then several quantitative models of those samples contained deltamethrin pesticide were built with partial least squares（PLS） .The results showed that the best model was built with the differential spectrum.The correlation coefficient of calibration （Rc） and the correlation coefficient of validation （Rp）of the best model were 0.9908,0.9552 respectively.The root mean square error RMSEC and the root mean square error RMSECV were 0.0802,0.23 respectively. All results indicated that this method can be used for a rapid and nondestructive detection of deltamethrin on spinach, as well as other agricultural products.

关 键 词： 无损检测 菠菜 溴氰菊酯