2021
DOI: 10.1007/s00604-021-05025-3
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Rapid field trace detection of pesticide residue in food based on surface-enhanced Raman spectroscopy

Abstract: Surface-enhanced Raman spectroscopy is an alternative detection tool for monitoring food security. However, there is still a lack of a conclusion of SERS detection with respect to pesticides and real sample analysis, and the summary of intelligent algorithms in SERS is also a blank. In this review, a comprehensive report of pesticides detection using SERS technology is given. The SERS detection characteristics of different types of pesticides and the influence of substrate on inspection are discussed and compa… Show more

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Cited by 38 publications
(15 citation statements)
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References 182 publications
(190 reference statements)
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“…Currently, the reports of food safety testing using Raman spectrum have triggered a great interest (Pan et al., 2022; Z. Wu et al., 2021; C. Ye et al., 2022). At present, there are many reports on pesticides (D. Zhang, Liang, et al., 2021), veterinary drugs (Rahman et al., 2021), and other harmful substances (Girmatsion et al., 2021; Jiang et al., 2021; X. Kong et al., 2017) in food safety detection based on SERS technology. Compared with traditional substrates, PCs are not only greener to prepare but also have a periodic and orderly surface structure and a larger surface area, which are conducive to generating more Raman hotspots and improving Raman enhancement effects.…”
Section: Applicationsmentioning
confidence: 99%
See 1 more Smart Citation
“…Currently, the reports of food safety testing using Raman spectrum have triggered a great interest (Pan et al., 2022; Z. Wu et al., 2021; C. Ye et al., 2022). At present, there are many reports on pesticides (D. Zhang, Liang, et al., 2021), veterinary drugs (Rahman et al., 2021), and other harmful substances (Girmatsion et al., 2021; Jiang et al., 2021; X. Kong et al., 2017) in food safety detection based on SERS technology. Compared with traditional substrates, PCs are not only greener to prepare but also have a periodic and orderly surface structure and a larger surface area, which are conducive to generating more Raman hotspots and improving Raman enhancement effects.…”
Section: Applicationsmentioning
confidence: 99%
“…Ye et al, 2022). At present, there are many reports on pesticides (D. Zhang, Liang, et al, 2021), veterinary drugs (Rahman et al, 2021), and other harmful substances (Girmatsion et al, 2021;Jiang et al, 2021;X. Kong et al, 2017) in food safety detection based on SERS technology.…”
Section: Raman Spectrummentioning
confidence: 99%
“…However, conventional Raman spectroscopy is extremely weak, susceptible to fluorescence interference, and has low detection sensitivity, which limits its application. Surface-enhanced Raman spectroscopy (SERS) is a method that uses light to interact with nanostructured materials such as gold and silver to produce a strong surface plasmon resonance effect, which can significantly enhance the Raman signal of molecules adsorbed on the surface of nanostructures to obtain ultra-sensitive fingerprints of the sample itself or Raman probe molecules ( Zhang et al, 2021a ; Berry et al, 2021 ; Liu et al, 2021b ). SERS has become a promising technique for bio-detection ( Wang et al, 2021a ; Wang et al, 2021b ) by compensating for the shortcomings of conventional Raman spectroscopy with local enhancement of up to 10 14 in the plasma gap and sharp protrusions.…”
Section: Introductionmentioning
confidence: 99%
“…Therefore, it is crucial to achieve rapid detection and reliable quantification of carbaryl. Traditional detection methods, such as chromatography [ 9 , 10 , 11 , 12 ], surface-enhanced Raman spectroscopy [ 13 , 14 , 15 ], immunoassay [ 16 , 17 ], etc., have been developed very well, with high sensitivity and accuracy in the determination of pesticide residues in water and agricultural products. However, the limitations lie in the complex sample handling process, the use of highly toxic organic solvents and the expensive and complex instruments that require professional testing [ 18 , 19 , 20 ].…”
Section: Introductionmentioning
confidence: 99%