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Proceedings Paper

Near-infrared microscopy imaging for quantitative analysis of active component in counterfeit imidacloprid
Author(s): Yue Huang; Jinli Cao; Shengfeng Ye; Jia Duan; Lijun Wu; Qianqian Li; Shungeng Min
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Paper Abstract

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.

Paper Details

Date Published: 15 November 2011
PDF: 8 pages
Proc. SPIE 8335, 2012 International Workshop on Image Processing and Optical Engineering, 83351W (15 November 2011); doi: 10.1117/12.917593
Show Author Affiliations
Yue Huang, China Agricultural Univ. (China)
Jinli Cao, Tobacco Corp. of Dali (China)
Shengfeng Ye, China Agricultural Univ. (China)
Jia Duan, China Agricultural Univ. (China)
Lijun Wu, China Agricultural Univ. (China)
Qianqian Li, China Agricultural Univ. (China)
Shungeng Min, China Agricultural Univ. (China)

Published in SPIE Proceedings Vol. 8335:
2012 International Workshop on Image Processing and Optical Engineering
Hai Guo; Qun Ding, Editor(s)

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