化学
色谱法
自来水
数字图像
图像处理
人工智能
环境工程
图像(数学)
计算机科学
工程类
作者
Karthikumar Sankar,D. Lenisha,G. Janaki,J. Juliana,R. Shyam Kumar,M. Chengathir Selvi,G. Srinivasan
出处
期刊:Talanta
[Elsevier]
日期:2019-09-30
卷期号:208: 120408-120408
被引量:35
标识
DOI:10.1016/j.talanta.2019.120408
摘要
A paper-based device (PBD) for the detection of chlorpyrifos pesticide at field application was fabricated based on the principles of enzyme inhibition and image processing. Rhizopus niveus lipase, p-nitrophenol palmitate and Whatman No.1 paper were used as an enzyme, substrate and support matrix, respectively. The performance of functionalized PBD was tested for lateral flow assay reaction in pure water (negative control), artificial pesticide water (positive control) and selected fruits and vegetables wash water (test). The digital image of the PBD after the test was captured using an android smartphone and analyzed in MATLAB software. Different colour space models such as, grey, RGB, HSV and YCbCr were studied and the Cb coordinate was chosen for its higher linearity (R2 = 0.988) with pesticide concentration. Experimental variations such as paper length, relative concentration ratio of the substrate and enzyme were investigated to minimize the product cost and analysis time. The developed PBD showed a significant response over wide range of sample solution's pH and operational temperature. Further, a long-term storage stability was measured for developed PBD. The LOD and LOQ were found to be 0.065 mgL-1 and 0.198 mgL-1. The results obtained from newly developed image processing method showed 92.8% accuracy with microtiter plate assay. Higher MRL was determined in the wash water of cauliflower, grapes, coriander leaves, brinjal and bitter guard. Overall, the developed paper biosensor was precise, cost effective and most suitable for field applications.
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