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Aptamer–gold nanoparticle-based lab-in-a-tube colorimetric detection of malathion: evaluation with classical and digital readout techniques

Jun 2026 · Turkish journal of chemistry · Vol 50, pp. 359 - 368 · 0 citations · 36 references
Medicine

Abstract

Colorimetric biosensing devices represent an important class of point-of-care (POC) diagnostics due to their ability to provide visible test outputs, their ease of integration with smartphone-based sensing, and their portability for field testing. In the context of agrifood safety, there is a growing need for portable, robust, and cost-effective detection devices. Pesticide residues can be present in a wide range of environmental and food samples, from water resources to fruits and vegetables, resulting in an increasing global demand for on-site testing. Colorimetric assays, when combined with smartphone-based sensing, can effectively address these needs. In this work, the aggregation-induced color change response of aptamer–gold nanoparticle conjugates was exploited to design a lab-in-a-tube colorimetric assay for the detection of malathion. The performance of the assay was evaluated using both a conventional spectrophotometric method as a laboratory-based reference and a smartphone-based readout supported by color intensity analysis as a portable detection approach. Color responses were quantified using both a mobile application and computer software across different color channels. The smartphone-based readout yielded a limit of detection (LOD) of 5.14 mg/mL and a linear detection range of 0.02–100 mg/mL with a correlation coefficient (R2) of 0.9981 for the mobile application, while the computer software-based analysis exhibited an LOD of 0.88 mg/mL, a linear range of 0.02–50 mg/mL, and an R2 of 0.9789. In comparison, the spectrophotometric method showed an LOD of 1.67 mg/mL, a linear range of 0.02–100 mg/mL, and an R2 of 0.9948, confirming the reliability of the smartphone-based approaches. The results demonstrate that the colorimetric assay developed can be successfully integrated with smartphones for field-testing applications, while providing a competitive LOD comparable to laboratory-based methods.

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