基于近红外光谱技术的微量有机磷农药的快速检测  

Rapid determination of ppm-order concentration of organophosphorus pesticide based on near-infrared spectroscopy

作　　者：陈菁菁[1] 李永玉[1] 吴建虎[1] 彭彦昆[1] 

机构地区：[1]中国农业大学工学院,北京100083

出　　处：《食品安全质量检测学报》2009年第1期45-50,共6页Journal of Food Safety and Quality

基　　金：国家自然科学基金(30771244);北京市自然科学基金(6082016);国家863高技术研究发展计划(2008AA10Z210)资助项目

摘　　要：针对现有的微量农药检测手段费时、复杂、前处理过程繁琐等不足,研究利用近红外光谱技术检测微量农药。制备两种不同的样品:不同浓度梯度的液体农药溶液样品和滤纸农药干燥样品,通过采取不同的光谱预处理手段,对比其相关系数和交叉验证均方差选择最适合的光谱预处理方法,采用偏最小二乘回归法建立预测模型。最后得出结论:滤纸农药干燥样品由于去除了绝大部分的水分使得检测精度相比较液体农药溶液样品有较大的提高,预测相关系数达到0.989,预测残差值为0.153,且相对分析误差为6.812,可以进行对农药浓度的定量检测。The traditional methods for detection of pesticide concentration in ppm-order are time-consuming,complicated,and required to do a lot of pretreatment processes.In this study,near-infrared spectroscopy was used to develop a new detection method for measuring trace chemicals,which probably could be useful for detection of pesticide residue in vegetable.There were two sets of samples.One was pesticide solution prepared by dissolving the commercial pesticide into distilled water at different concentration,and the other one was a set of filter paper samples prepared by pipetting the solution onto the filter paper and then evaporated by vacuum drying oven.Different methods for pre-processing spectral signal were performed to find a better pre-processing method through comparison their prediction results with the correlation coefficient(R) and the root mean square error of cross-validation(RMSEcv).Partial least squares regression(PLSR) method was used to establish prediction models.Prediction results indicated that the filter paper samples had higher prediction accuracy than liquid pesticide samples because the water of filter paper samples was evaporated.The models were able to predict the concentration of chlorpyrifos with R=0.989,RMSEP=0.153.It can be used to prediction the pesticide concentration in quantitative limitation.

关 键 词：近红外光谱技术 偏最小二乘回归 有机磷农药 快速检测 

分 类 号：TQ450.7[化学工程—农药化工]