A novel detector using a fluorescent sensor array and discrimination of pesticides

A novel detector using a fluorescent sensor array and discrimination of pesticides A novel, simple, and rapid detector using a fluorescent sensor array for discrimination and quantification of different concentrations (ppb level) of pesticides was proposed in this paper. Employing porphyrin, porphyrin derivatives, and chemically responsive dyes as the sensing elements, the developed sensor array based on a cross-responsive mechanism showed a unique pattern of fluorescence changes upon the reaction that lasted just 10 min. The eigenvalues from raw fluorescence spectra were analyzed via a pattern recognition algorithm, including hierarchical cluster analysis (HCA), principal component analysis (PCA), and back-propagation neural network (BPNN). The results showed that HCA, which were used to assess the feasibility and effectiveness of discrimination of the fluorescent sensor array, revealed a distinct separation between different pesticides. PCA and BPNN were used for automatically predicting the concentration of pesticides, and the recovery was 91.29–109.81 % while the lowest relative standard deviation was up to 3.12 %. It indicates a detector based on the fluorescent sensor array is a rapid and feasible sensing platform for the discrimination and quantitative analysis of pesticides, and also shows the possibilities in the related fields of pesticides identification and detection. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Research on Chemical Intermediates Springer Journals

A novel detector using a fluorescent sensor array and discrimination of pesticides

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Publisher
Springer Journals
Copyright
Copyright © 2016 by Springer Science+Business Media Dordrecht
Subject
Chemistry; Catalysis; Physical Chemistry; Inorganic Chemistry
ISSN
0922-6168
eISSN
1568-5675
D.O.I.
10.1007/s11164-016-2541-8
Publisher site
See Article on Publisher Site

Abstract

A novel, simple, and rapid detector using a fluorescent sensor array for discrimination and quantification of different concentrations (ppb level) of pesticides was proposed in this paper. Employing porphyrin, porphyrin derivatives, and chemically responsive dyes as the sensing elements, the developed sensor array based on a cross-responsive mechanism showed a unique pattern of fluorescence changes upon the reaction that lasted just 10 min. The eigenvalues from raw fluorescence spectra were analyzed via a pattern recognition algorithm, including hierarchical cluster analysis (HCA), principal component analysis (PCA), and back-propagation neural network (BPNN). The results showed that HCA, which were used to assess the feasibility and effectiveness of discrimination of the fluorescent sensor array, revealed a distinct separation between different pesticides. PCA and BPNN were used for automatically predicting the concentration of pesticides, and the recovery was 91.29–109.81 % while the lowest relative standard deviation was up to 3.12 %. It indicates a detector based on the fluorescent sensor array is a rapid and feasible sensing platform for the discrimination and quantitative analysis of pesticides, and also shows the possibilities in the related fields of pesticides identification and detection.

Journal

Research on Chemical IntermediatesSpringer Journals

Published: Apr 9, 2016

References

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