Title : Pesticide Residues Identification by Optical Spectrum in the Time-Sequence of Enzyme Inhibitors Performed on Microfluidic Paper-Based Analytical Devices (microPADs) - Yang_2019_Molecules_24_ |
Author(s) : Yang N , Shaheen N , Xie L , Yu J , Ahmad H , Mao H |
Ref : Molecules , 24 : , 2019 |
Abstract :
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. |
PubMedSearch : Yang_2019_Molecules_24_ |
PubMedID: 31269660 |
Yang N, Shaheen N, Xie L, Yu J, Ahmad H, Mao H (2019)
Pesticide Residues Identification by Optical Spectrum in the Time-Sequence of Enzyme Inhibitors Performed on Microfluidic Paper-Based Analytical Devices (microPADs)
Molecules
24 :
Yang N, Shaheen N, Xie L, Yu J, Ahmad H, Mao H (2019)
Molecules
24 :