A deep learning-enabled smartphone platform for rapid and sensitive colorimetric detection of dimethoate pesticide

Liu, Shuai; Zhao, Jingkai; Wu, Junfeng; Wang, Ling; Hu, Jiandong; Li, Shixin; Zhang, Hao

doi:10.1007/s00216-023-04978-z

Cited by 5 publications

(1 citation statement)

References 36 publications

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“…Currently, several methods are used to detect dimethoate including high-performance liquid chromatography (HPLC) [9,10], gas chromatography (GC) with mass spectrometry (MS) [11,12], capillary electrophoresis-mass spectrometry (CE-MS) [13], thin layer chromatography [14], an electrochemical sensor [15,16] and a biosensor [17,18]. These methods are sophisticated, sensitive, and accurate for the determination of dimethoate at low levels.…”

Section: Introductionmentioning

confidence: 99%

Ti3C2Tx MXene-Based Fluorescent Aptasensor for Detection of Dimethoate Pesticide

Li,

Pu,

Wei

2024

Biosensors

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Dimethoate contaminants in food pose a threat to human health. Rapid and sensitive trace detection methods are required to keep food safe. In this study, a novel fluorescent aptasensor was developed for the sensitive detection of dimethoate based on carbon quantum dots labeled with double-stranded DNA (CQDs−apt−cDNA) and Ti3C2Tx flakes. Under optimal conditions, the aptasensor showed a good linear range of 1 × 10−9 to 5 × 10−5 M for dimethoate with a coefficient of determination (R2) of 0.996. Besides, a low detection limit of 2.18 × 10−10 M was obtained. The aptasensor showed high selectivity in interference samples and good reproducibility with an RSD of 3.06% (<5%) for dimethoate detection. Furthermore, the proposed aptasensor was applied to the detection of dimethoate in apple juice and tap water with satisfactory recoveries from 96.2 to 104.4%. Because of these benefits, this aptasensor has the potential and promise for detecting food contaminants in the food industry.

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