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Publication
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| Title of Article |
A machine learning colorimetric biosensor based on acetylcholinesterase and silver nanoparticles for the detection of dichlorvos pesticide |
| Date of Acceptance |
3 May 2022 |
| Journal |
| Title of Journal |
Materials Chemistry Frontiers |
| Standard |
SCOPUS |
| Institute of Journal |
Royal Society of Chemistry |
| ISBN/ISSN |
- |
| Volume |
2022 |
| Issue |
- |
| Month |
May |
| Year of Publication |
2022 |
| Page |
Mater. Chem. Front., 2022,6, 1487-1498 |
| Abstract |
An uncomplicated and rapid colorimetric biosensor for the detection of highly toxic organophosphates (OPs) is developed, using the pesticide dichlorvos as a representative OP. Dichlorvos (DCV) detection is based on its inhibition of the catalytic activity of acetylcholinesterase on acetylthiocholine, which in turn is coupled to a reversible aggregation of citrate-capped silver nanoparticles (c-AgNPs) that gives strong color changes in solution. This color change can be observed by the naked eye for rapid screening. It can also be observed by UV-vis spectrometry, allowing quantification of DCV over a linear range of 1–7 μM with a limit of detection (LOD) and limit of quantitation (LOQ) of 0.65 μM and 3.21 μM. We show further that implementing a trained image processing convolution neural network (CNN) gives a superior quantitative performance, with DCV assay accuracy of 97.6% and assay range from 0–60 μM, using a smartphone for image collection and analysis. This machine learning-based DCV assay may find application in field studies to obtain rapid but also quantitative information about contamination in, for example, water and juices. |
| Keyword |
silver nanoparticles, acetylcholinesterase, acetylthiocholine chloride, colorimeter, dichlorvos, biosensor, machine learning |
| Author |
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| Reviewing Status |
ไม่มีผู้ประเมินอิสระ |
| Status |
ตีพิมพ์แล้ว |
| Level of Publication |
นานาชาติ |
| citation |
false |
| Part of thesis |
true |
| Attach file |
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| Citation |
0
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Journal Publication
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