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- W3048281329 endingPage "127796" @default.
- W3048281329 startingPage "127796" @default.
- W3048281329 abstract "Trace detection of toxic chemicals in foodstuffs is of great concern in recent years. Surface-enhanced Raman scattering (SERS) has drawn significant attention in the monitoring of food safety due to its high sensitivity. This study synthesized signal optimized flower-like silver nanoparticle-(AgNP) with EF at 25 °C of 1.39 × 106 to extend the SERS application for pesticide sensing in foodstuffs. The synthesized AgNP was deployed as SERS based sensing platform to detect methomyl, acetamiprid-(AC) and 2,4-dichlorophenoxyacetic acid-(2,4-D) residue levels in green tea via solid-phase extraction. A linear correlation was twigged between the SERS signal and the concentration for methomyl, AC and 2,4-D with regression coefficient of 0.9974, 0.9956 and 0.9982 and limit of detection of 5.58 × 10−4, 1.88 × 10−4 and 4.72 × 10−3 µg/mL, respectively; the RSD value < 5% was recorded for accuracy and precision analysis suggesting that proposed method could be deployed for the monitoring of methomyl, AC and 2,4-D residue levels in green tea." @default.
- W3048281329 created "2020-08-13" @default.
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- W3048281329 date "2021-02-01" @default.
- W3048281329 modified "2023-09-23" @default.
- W3048281329 title "Signal optimized rough silver nanoparticle for rapid SERS sensing of pesticide residues in tea" @default.
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- W3048281329 doi "https://doi.org/10.1016/j.foodchem.2020.127796" @default.
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