scholarly journals Detection of pesticide residue distribution on fruit surfaces using surface-enhanced Raman spectroscopy imaging

RSC Advances ◽  
2018 ◽  
Vol 8 (9) ◽  
pp. 4726-4730 ◽  
Author(s):  
Jiannan Chen ◽  
Daming Dong ◽  
Song Ye
Keyword(s):  
Raman Spectroscopy ◽  
Pesticide Residue ◽  
Pesticide Residues ◽  
Quantitative Measurement ◽  
Surface Enhanced Raman Spectroscopy ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

Surface-enhanced Raman spectroscopy (SERS) is an emerging technique for the detection of pesticide residues on food surfaces, permitting quantitative measurement of pesticide residues without pretreating the sample.

scholarly journals Rapid Detection of Pesticide Residues in Paddy Water Using Surface-Enhanced Raman Spectroscopy

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 506 ◽  
Author(s):  
Shizhuang Weng ◽  
Wenxiu Zhu ◽  
Ronglu Dong ◽  
Ling Zheng ◽  
Fang Wang
Keyword(s):  
Raman Spectroscopy ◽  
Pesticide Residue ◽  
Pesticide Residues ◽  
Rapid Detection ◽  
Surface Enhanced Raman Spectroscopy ◽  
Support Vector ◽  
Chemometric Methods ◽  
Paddy Water ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

Pesticide residue in paddy water is one of the main factors affecting the quality and safety of rice, however, the negative effect of this residue can be effectively prevented and reduced through early detection. This study developed a rapid detection method for fonofos, phosmet, and sulfoxaflor in paddy water through chemometric methods and surface-enhanced Raman spectroscopy (SERS). Residue from paddy water samples was directly used for SERS measurement. The obtained spectra from the SERS can detect 0.5 mg/L fonofos, 0.25 mg/L phosmet, and 1 mg/L sulfoxaflor through the appearance of major characteristic peaks. Then, we used chemometric methods to develop models for the intelligent analysis of pesticides, alongside the SERS spectra. The classification models developed by K-nearest neighbor identified all of the samples, with an accuracy of 100%. For the quantitative analysis, the partial least squares regression models obtained the best predicted performance for fonofos and sulfoxaflor, and the support vector machine model provided optimal results, with a root-mean-square error of validation of 0.207 and a coefficient of determination of validation of 0.99952, for phosmet. Experiments for actual contaminated samples also showed that the above models predicted the pesticide residue values with high accuracy. Overall, using SERS with chemometric methods provided a simple and convenient approach for the detection of pesticide residues in paddy water.

Inspection of pesticide residues on food by surface-enhanced Raman spectroscopy

2004 ◽  
Author(s):  
Chetan Shende ◽  
Alan Gift ◽  
Frank Inscore ◽  
Paul Maksymiuk ◽  
Stuart Farquharson
Keyword(s):  
Raman Spectroscopy ◽  
Pesticide Residues ◽  
Surface Enhanced Raman Spectroscopy ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

Fabrication of sensitive silver-decorated cotton swabs for SERS quantitative detection of mixed pesticide residues in bitter gourds

2020 ◽  
Vol 44 (29) ◽  
pp. 12779-12784
Author(s):  
Lili Kong ◽  
Meizhen Huang ◽  
Jie Chen ◽  
Mengshi Lin
Keyword(s):  
Raman Spectroscopy ◽  
Pesticide Residues ◽  
Rapid Detection ◽  
Environmentally Friendly ◽  
Surface Enhanced Raman Spectroscopy ◽  
Quantitative Detection ◽  
Fabrication Method ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

This study developed a simple, efficient and environmentally friendly fabrication method for surface-enhanced Raman spectroscopy (SERS) wipers for the rapid detection of individual and mixed pesticide residues in actual samples.

In situ analysis of pesticide residues on the surface of agricultural products via surface-enhanced Raman spectroscopy using a flexible Au@Ag–PDMS substrate

2019 ◽  
Vol 43 (33) ◽  
pp. 13075-13082 ◽  
Author(s):  
Hang Zhao ◽  
Wuliji Hasi ◽  
Nan Li ◽  
Xuanyu Sha ◽  
Shuang Lin ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Pesticide Residues ◽  
Surface Enhanced Raman Spectroscopy ◽  
Agricultural Products ◽  
In Situ Analysis ◽  
Pdms Substrate ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

In situ analysis of pesticide residues on the surface of agricultural products via surface-enhanced Raman spectroscopy using a flexible Au@Ag–PDMS substrate.

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