Quantification of deltamethrin residues in wheat by Ag@ZnO NFs-based surface-enhanced Raman spectroscopy coupling chemometric models

Deltamethrin, one of the most toxic pyrethroids, is commonly used to inhibit pests in wheat. However, the trace levels of deltamethrin in wheat is alarming to human health. In this study, surface-enhanced Raman spectroscopy (SERS)-active silver nanoparticles-plated-zinc oxide nanoflowers (Ag@ZnO NFs) nano-sensor were employed for rapid and sensitive quantification of deltamethrin in wheat. To sufficiently utilize the chemical-related information in SERS spectra, various spectral pretreatment and chemometric models were studied. The mean centering (MC) coupling successive projection algorithm-partial least squares regression (SPA-PLS) provided optimal predictive performance (correlation coefficient of prediction (Rp) = 0.9736 and residual predictive deviation (RPD) = 4.75). The proposed method achieved the limit of detection (LOD) = 0.16 mu g.kg(-1), the recovery of predicted results was in the range of 96.33-109.17% and the relative standard deviation (RSD) was < 5%. The overall results suggested that SERS based Ag@ZnO NFs combined with MC-SPA-PLS could be an easy and efficient method to quantify deltamethrin residue levels in wheat.

Automated summary

In this study, a nano-sensor using SERS-active silver nanoparticles-plated-zinc oxide nanoflowers was employed to quantify deltamethrin in wheat rapidly and sensitively. By utilizing mean centering coupled with successive projection algorithm-partial least squares regression, optimal predictive performance was achieved with low limit of detection, high recovery rates, and low relative standard deviation. The results suggested that the method could effectively quantify deltamethrin residue levels in wheat.