Rapid Detection of Carbendazim Residue in Apple Using Surface-Enhanced Raman Scattering and Coupled Chemometric Algorithm

Xiaowei Huang; Ning Zhang; Zhihua Li; Jiyong Shi; Haroon Elrasheid Tahir; Yue Sun; Yang Zhang; Xinai Zhang; Melvin Holmes; Xiaobo Zou

doi:10.3390/foods11091287

Rapid Detection of Carbendazim Residue in Apple Using Surface-Enhanced Raman Scattering and Coupled Chemometric Algorithm

Foods. 2022 Apr 28;11(9):1287. doi: 10.3390/foods11091287.

Authors

Xiaowei Huang^{1

2}, Ning Zhang^{1

2}, Zhihua Li^{1

2}, Jiyong Shi^{1

2}, Haroon Elrasheid Tahir^{1

2}, Yue Sun^{1

2}, Yang Zhang^{1

2}, Xinai Zhang^{1

2}, Melvin Holmes^{3

4}, Xiaobo Zou^{1

2

4

5}

Affiliations

¹ School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China.
² School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China.
³ School of Food Science and Nutrition, University of Leeds, Leeds LS2 9JT, UK.
⁴ International Joint Research Laboratory of Intelligent Agriculture and Agri-Products Processing, Jiangsu Education Department, Jiangsu University, Zhenjiang 212013, China.
⁵ Collaborative Innovation Center for Modern Grain Circulation and Safety, College of Food Science and Engineering, Nanjing University of Finance and Economics, Nanjing 210023, China.

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 (R_P) 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.

Keywords: Ag-NPs @PAN-nanohump arrays; apple; bootstrapping soft shrinkage-partial least squares (BOSS-PLS); carbendazim; surface-enhanced Raman spectroscopy (SERS).

Abstract

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