Research On High-precision Paper-based Microfluidic Photoelectric Detection Method

In China,there are more than 100 thousand people are poisoned by accidental ingestion of fruits,vegetables and other foods containing pesticide residue every year,and the fatality rate is about 20%.Therefore,the pesticide residue detection has become a hot issue.The pesticide residues detection equipment at present cannot both satisfy the demand of high precision and portability at the same time.This article proposes a microfluidic based paper chip equipped with photoelectric technology to achieve the equipment integration during the detection.In this article,the modeling and analysis of the factors that affect the chip structure and detection accuracy of the paper-based microfluidic chip systems will be discussed.The research is divided into the following three aspects.Firstly,the basic principle of the enzyme inhibition biochemical reaction on the paper-based microfluidic chip is introduced,and the reflective photoelectric detection as well as fluorescence photoelectric detection are utilized to collect the color information and the change of material molecular.The principle of detection and the factors that affect detection precision are deduced.Secondly,efforts are devoted on researches of reflective photoelectric paper-based microfluidic chip(RPPMC)and fluorescent paper-based microfluidic chip(FPMC).In order to get the optimum chip structure,the influencing factors of internal structure of RPPMC and FPMC such as sample diameter,micro-mixing mechanism and distance,contact area and so on are analyzed and modeled.At the same time,we will compare and determine the final material to fabricate chip and the corresponding production plan of chip.In order to improve the detection efficiency,the parameters that influence RPPMC such as reaction time,p H,detection temperature,light wave length,detection temperature,and parameters that influence FPMC such as the amount of enzyme affecting,excitation wavelength,detection distance are studied.This provides the theoretical basis for the portable integrated detection device.Thirdly,according to the analysis results,the test platform of RPPMC and FPMC methods are built.The BP neural network algorithm is used to compensate the noise error factors existing in these two methods,and it can improve the measurement accuracy.According to the compensation model,the linear regression curves of RPPMC and FPMC are established based on two typical organophosphorus pesticides of trichlorfon and parathion.And this paper also proposed the test of repeatability and recovery rate of strawberry and spinach samples to verify the reliability of the two methods.The experimental results show that the correlation coefficients of RPPMC and FPMC methods for trichlorfon are 0.982 and 0.996 after error compensation,and the detection limits are 0.010mg/L and 0.007mg/L.The correlation coefficients for parathion are 0.984 and 0.978,and the detection limits are 0.014mg/L and 0.012mg/L,which outclass the current national testing standards.After the actual sample detection,the relative standard deviations of RPPMC assay for strawberry and spinach are from 1.5% to 6.2% respectively,and for FPMC,the relative standard deviations of RPPMC assay for strawberry and spinach are from 3.9% to 7.1%.This accounts for the high precision of these two detection systems that could meet the requirement.