ArticleFoods (Basel, Switzerland)2022
Copper-Modified Double-Emission Carbon Dots for Rapid Detection of Thiophanate Methyl in Food.
Article in Foods (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Pre-Reduction-Activated Carbon-Based Zinc Vanadate Nanosheet Composite with Zn-O-V Performance Synergy for Machine Learning-Enabled Multiplex Pesticide Detection.Nanomaterials (Basel, Switzerland) · 2026Article
- Antioxidant Performance and Characterization Comparison of Carbon Dots Derived from Agricultural Waste Pineapple Peel.Foods (Basel, Switzerland) · 2026Article
- Sensitive and selective colorimetric detection of thiophanate-methyl based on a novel Ru-FeMikrochimica acta · 2025Article
- MOF-based Ag NPs/CoMikrochimica acta · 2024Article
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Authors and funding
7 authors.
Funding
Abstract
The detection of food safety and quality is very significant throughout the food supply. Stable dual-emission copper-modified fluorescent carbon dots (Cu-CDs) were successfully synthesized by a simple and environment-friendly hydrothermal, which was used for the real-time detection of pesticide residues in agricultural products. By optimizing the reaction conditions, Cu-CDs showed two emission peaks, with the highest fluorescence intensities at 375 and 450 nm. The structure, chemical composition and optical properties of Cu-CDs were investigated by XRD, TEM and IR. The results showed that thiophanate methyl (TM) could induce fluorescence quenching of Cu-CDs with no other ligands by the electron transfer through π-π stacking. The synchronous response of the dual-emission sensor enhanced the specificity of TM, which showed remarkable anti-interference capability. The fluorescence quenching degree of Cu-CDs had a good linear relationship with the TM concentration; the low detection limit for a pear was 0.75 μM, and for an apple, 0.78 μM. The recoveries in the fruit samples were 79.70-91.15% and 81.20-93.55%, respectively, and the relative standard deviations (RSDs) were less than 4.23% for the pear and less than 3.78% for the apple. Thus, our results indicate the feasibility and reliability of our methods in detecting pesticide residues in agricultural products.
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