Open AccessDesign of multilayer microfluidic paper chip and its visual detection of pesticide residues
Author(s) -
Li zhi Li,
Han Ping Mao
Publication year - 2020
Publication title -
journal of advances in agriculture
Language(s) - English
Resource type - Journals
ISSN - 2349-0837
DOI - 10.24297/jaa.v11i.8861
Subject(s) - acetamiprid , repeatability , pesticide residue , detection limit , microfluidic chip , chromatography , mixing (physics) , pesticide , chip , microfluidics , chemistry , biological system , mathematics , computer science , materials science , nanotechnology , biology , physics , imidacloprid , quantum mechanics , agronomy , telecommunications
With the increase of China's grain production, the use of pesticides is gradually increasing. Traditional pesticide detection takes a long time and requires expensive experimental instruments, which is not conducive to the rapid and accurate detection of pesticide residues in the field. To solve this problem, this paper proposes a visual detection method of pesticide residues based on multi-layer microfluidic paper chips. The internal channel structure of paper chip is designed from the perspective of efficient mixing. Through the simulation of the mixed effect of three kinds of staggered channel structures, which are arc type, triangle type, and ladder type, the "ladder-type h-0.3, s-2.6" is selected as the best-staggered structure, and the mixing strength is 0.91534. The best simulation structure was tested by a colored reagent, and the image processing of 15 test results was carried out with MATLAB. The average mixing strength was 0.84, and the and the standard deviation was 0.022. The visual detection experiment of acetamiprid and profenofos in cabbage samples was carried out by using the deviceThe detection range of acetamiprid was 4~72 μg/kg, and the detection range of profenofos was 3~54 μg/kg . The recovery of acetamiprid was 75%~85%, and the recovery of profenofos was 80%~90%. The detection range and recovery rate indicate that the device has high repeatability and accuracy in the actual sample detection