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Near-infrared microscopy imaging for quantitative analysis of active component in counterfeit imidacloprid

机译:近红外显微成像技术定量分析假冒吡虫啉中的有效成分

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Near-infrared (NIR) imaging systems simultaneously record spectral and spatial information. Near-infrared imaging was applied to the identification of imidacloprid in both artificially mixed samples and commercial formulation in this study. The distributions of technical imidacloprid and additive in the heterogeneous counterfeit were obtained by the relationship imaging (RI) mode. Furthermore a series of samples which consisted of different contents of uniformly distributed imidacloprid were prepared and three data cubes were generated at each content. Extracted spectra from those images were imported to establish the partial least squares model. The model's results were: R2 99.21%, RMSEC 0.0306, RMSECV 0.0183, RMSECV/mean value 0.0348 and RSEP 0.0784. The prediction relative error of commercial formulation is 0.0680, indicating the predicted value was correlated to the real content. Lastly the chemical value reconstruction image of imidacloprid formulation products was calculated by MATLAB program. NIR microscopy imaging manifests herein its potential in qualitatively identifying the active component in counterfeit pesticide and quantifying the active component in scanned image.
机译:近红外(NIR)成像系统同时记录光谱和空间信息。本研究将近红外成像技术用于人工混合样品和商业制剂中吡虫啉的鉴定。通过关系成像(RI)模式获得了异虫类中工业吡虫啉和添加剂的分布。此外,制备了由不同含量的吡虫啉均匀分散组成的一系列样品,并在每个含量下生成了三个数据立方体。从这些图像提取的光谱被导入以建立偏最小二乘模型。该模型的结果为:R2 99.21%,RMSEC 0.0306,RMSECV 0.0183,RMSECV /平均值0.0348和RSEP 0.0784。商业配方的预测相对误差为0.0680,表明预测值与实际含量相关。最后用MATLAB程序计算吡虫啉制剂产品的化学值重建图像。 NIR显微镜成像在此显示出其在定性鉴定假冒农药中的活性成分和定量扫描图像中的活性成分方面的潜力。

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