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Signal optimized rough silver nanoparticle for rapid SERS sensing of pesticide residues in tea.
- Source :
-
Food chemistry [Food Chem] 2021 Feb 15; Vol. 338, pp. 127796. Date of Electronic Publication: 2020 Aug 10. - Publication Year :
- 2021
-
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 × 10 <superscript>6</superscript> 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 <superscript>-4</superscript> , 1.88 × 10 <superscript>-4</superscript> and 4.72 × 10 <superscript>-3</superscript> 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.<br />Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2020 Elsevier Ltd. All rights reserved.)
- Subjects :
- 2,4-Dichlorophenoxyacetic Acid analysis
Food Analysis instrumentation
Food Analysis methods
Methomyl analysis
Neonicotinoids analysis
Silver chemistry
Solid Phase Extraction
Food Contamination analysis
Metal Nanoparticles chemistry
Pesticide Residues analysis
Spectrum Analysis, Raman methods
Tea chemistry
Subjects
Details
- Language :
- English
- ISSN :
- 1873-7072
- Volume :
- 338
- Database :
- MEDLINE
- Journal :
- Food chemistry
- Publication Type :
- Academic Journal
- Accession number :
- 32805691
- Full Text :
- https://doi.org/10.1016/j.foodchem.2020.127796