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- Title
Rapid Detection of Carbendazim Residue in Apple Using Surface-Enhanced Raman Scattering and Coupled Chemometric Algorithm.
- Authors
Huang, Xiaowei; Zhang, Ning; Li, Zhihua; Shi, Jiyong; Tahir, Haroon Elrasheid; Sun, Yue; Zhang, Yang; Zhang, Xinai; Holmes, Melvin; Zou, Xiaobo
- Abstract
In order to achieve rapid and precise quantification detection of carbendazim residues, surface-enhanced Raman spectroscopy (SERS) combined with variable selected regression methods were developed. A higher sensitivity and greater density of "hot spots" in three-dimensional (3D) SERS substrates based on silver nanoparticles compound polyacrylonitrile (Ag-NPs @PAN) nanohump arrays were fabricated to capture and amplify the SERS signal of carbendazim. Four Raman spectral variable selection regression models were established and comparatively assessed. The results showed that the bootstrapping soft shrinkage-partial least squares (BOSS-PLS) method achieved the best predictive capacity after variable selection, and the final BOSS-PLS model has the correlation coefficient (RP) of 0.992. Then, this method used to detect the carbendazim residue in apple samples; the recoveries were 86~116%, and relative standard deviation (RSD) is less than 10%. The 3D SERS substrates combined with the BOSS-PLS algorithm can deliver a simple and accurate method for trace detection of carbendazim residues in apples.
- Subjects
SERS spectroscopy; CARBENDAZIM; CHEMOMETRICS; SILVER nanoparticles; SILVER compounds
- Publication
Foods, 2022, Vol 11, Issue 9, p1287
- ISSN
2304-8158
- Publication type
Article
- DOI
10.3390/foods11091287