4.6 Article

Pesticide Residues Identification by Optical Spectrum in the Time-Sequence of Enzyme Inhibitors Performed on Microfluidic Paper-Based Analytical Devices (μPADs)

Journal

MOLECULES
Volume 24, Issue 13, Pages -

Publisher

MDPI
DOI: 10.3390/molecules24132428

Keywords

organophosphorus and carbamates pesticide; pesticide residues rapid detection; time detection model

Funding

  1. Chinese National Natural Science Foundation [31701324, 31671584]
  2. Outstanding Youth Science Foundation of Jiangsu province [BK20180099]
  3. Zhenjiang Dantu Science and Technology Innovation Fund (Key R&D Program-Social Development) [SH2018003]
  4. Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)
  5. China Postdoctoral Science Foundation Project [2018M642182]
  6. Jiangsu Agricultural Science and Technology Innovation Fund [CX(18)3043]

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Pesticides vary in the level of poisonousness, while a conventional rapid test card only provides a general absence or not solution, which cannot identify the various genera of pesticides. In order to solve this problem, we proposed a seven-layer paper-based microfluidic chip, integrating the enzyme acetylcholinesterase (AChE) and chromogenic reaction. It enables on-chip pesticide identification via a reflected light intensity spectrum in time-sequence according to the different reaction efficiencies of pesticide molecules and assures the optimum temperature for enzyme activity. After pretreatment of figures of reflected light intensity during the 15 min period, the figures mainly focused on the reflected light variations aroused by the enzyme inhibition assay, and thus, the linear discriminant analysis showed satisfying discrimination of imidacloprid (Y = -1.6525X - 139.7500), phorate (Y = -3.9689X - 483.0526), and avermectin (Y = -2.3617X - 28.3082). The correlation coefficients for these linearity curves were 0.9635, 0.8093, and 0.9094, respectively, with a 95% limit of agreement. Then, the avermectin class chemicals and real-world samples (i.e., lettuce and rice) were tested, which all showed feasible graphic results to distinguish all the chemicals. Therefore, it is feasible to distinguish the three tested kinds of pesticides by the changes in the reflected light spectrum in each min (15 min) via the proposed chip with a high level of automation and integration.

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