近红外光谱分析技术在辛硫磷农药残留检测中的应用

采用近红外光谱分析法直接用于痕量农药辛硫磷的定量检测。通过引入一种样品预处理方法，将待测样品与硅胶混合，硅胶作为吸附剂，用来富集待测农药化合物，然后直接采集其漫反射光谱。用偏最小二乘(PLS)回归方法建立模型、留一交互验证法来对模型进行评价。通过两批次实验，浓度梯度为0.5 mg·L-1的21个样品的交互验证相关系数为0.958，RMSECV为 0.872 mg·L-1;浓度梯度为0.25 mg·L-1的41个样品的交互验证相关系数为0.924，RMSECV为1.15 mg·L-1。随着浓度梯度的降低，模型的预测能力有所下降，但模型的相关系数仍然较高。结果表明利用硅胶作为待测样品吸附剂的预处理方法，可以有效降低近红外光谱分析技术的检测限，在农药残留等低含量样品检测中有实际应用价值。

Application of Near-Infrared Spectroscopy to Detection of Pesticide Phoxim Residues

Near-infrared (NIR) spectroscopy technique was applied directly to the detection of pesticide phoxim residues. A sample pretreatment method was introduced. Samples were mixed with silica gel. Silica gel as a sorbent was employed to extract and enrich the low-concentration samples. Subsequently, diffuse reflection spectrum was measured on silica gel. Calibration models were developed using partial least square regression (PLSR) algorithm. Leave-one-out cross-validation was used to evaluate and compare the models. Two experiments were carried out, and the results show that 21 samples with the concentration gradient of 0.5 mg·L-1 exhibited a high correlation coefficient of cross-validation of 0.958, and a root mean square error of cross validation (RMSECV) of 0.872 mg·L-1, while 41 samples with the concentration gradient of 0.25 mg·L-1 gave a correlation coefficient of cross-validation of 0.924 and RMSECV of 1.15 mg·L-1. It is indicated that with the reduction in concentration gradient, the prediction capacity of models dropped, but there still existed a high correlation coefficient with the concentration of phoxim in the samples. The experiments proved that the sample pretreatment method with the introduction of silica gel as an absorber to enrich low concentration analyte was effective. The method was able to lower the detection limit of NIR. The developed technique has a potential application in low-concentration sample detection by NIR spectroscopy, such as pesticide residues.