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近红外光谱技术在辛硫磷农药残留检测中的应用

[Application of near-infrared spectroscopy to detection of pesticide phoxim residues].

作者信息

Shen Fei, Yan Zhan-ke, Ye Zun-zhong, Ying Yi-bin

机构信息

College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310029, China.

出版信息

Guang Pu Xue Yu Guang Pu Fen Xi. 2009 Sep;29(9):2421-4.

PMID:19950643
Abstract

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 x 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 x L(-1), while 41 samples with the concentration gradient of 0.25 mg x L(-1) gave a correlation coefficient of cross-validation of 0.924 and RMSECV of 1.15 mg x 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.

摘要

近红外(NIR)光谱技术被直接应用于农药辛硫磷残留的检测。介绍了一种样品预处理方法。将样品与硅胶混合。硅胶作为吸附剂用于提取和富集低浓度样品。随后,在硅胶上测量漫反射光谱。使用偏最小二乘回归(PLSR)算法建立校准模型。采用留一法交叉验证来评估和比较模型。进行了两个实验,结果表明,21个浓度梯度为0.5 mg x L(-1)的样品呈现出交叉验证的高相关系数0.958,交叉验证均方根误差(RMSECV)为0.872 mg x L(-1),而41个浓度梯度为0.25 mg x L(-1)的样品交叉验证相关系数为0.924,RMSECV为1.15 mg x L(-1)。结果表明,随着浓度梯度的降低,模型的预测能力下降,但与样品中辛硫磷的浓度仍存在较高的相关系数。实验证明,以硅胶作为吸附剂富集低浓度分析物的样品预处理方法是有效的。该方法能够降低近红外的检测限。所开发的技术在近红外光谱法检测低浓度样品(如农药残留)方面具有潜在应用。

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