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ISSN print edition: 0366-6352
ISSN electronic edition: 1336-9075
Registr. No.: MK SR 9/7
Published monthly
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Near-infrared imaging for quantitative analysis of active component in counterfeit dimethomorph using partial least squares regression
Yue Huang, Shun-Geng Min, Jin-Li Cao, Sheng-Feng Ye, and Jia Duan
College of Science, China Agricultural University, 100193 Beijing, China
E-mail: orange07@126.com
Abstract: Near-infrared (NIR) imaging systems simultaneously record spectral and spatial information. Near-infrared imaging was applied
to the identification of (E,Z)-4-(3-(4-chlorophenyl)-3-(3,4-dimethoxyphenyl)acryloyl)morpholine (dimethomorph) in both mixed samples and commercial formulation
in this study. The distributions of technical dimethomorph and additive in the heterogeneous counterfeit product were obtained
by the relationship imaging (RI) mode. Furthermore, a series of samples which consisted of different contents of uniformly
distributed dimethomorph were prepared and three data cubes were generated for each content. The spectra extracted from these
images were imported to establish the partial least squares model. The model’s evaluating indicators were: coefficient of
determination (R
2) 99.42 %, root mean square error of calibration (RMSEC) 0.02612, root mean square error of cross-validation (RMSECV) 0.01693,
RMSECVmean 0.03577, relative standard error of prediction (RSEP) 0.01999, and residual predictive deviation (RPD) 15.14. Relative error
of prediction of the commercial formulation was 0.077, indicating the predicted value correlated with the real content. The
chemical value reconstruction image of dimethomorph formulation products was calculated by a MATLAB program. NIR microscopy
imaging here manifests its potential in identifying the active component in the counterfeit pesticide and quantifying the
active component in its scanned image.
Keywords: near-infrared microscopy – micro-image quantitative analysis – partial least squares model – counterfeit dimethomorph
Full paper is available at www.springerlink.com.
DOI: 10.2478/s11696-012-0212-9
Chemical Papers 66 (11) 1065–1072 (2012)
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