Rapid identification and quantitative detection of organophosphorus pesticides on a portable device is of vital importance for food safety evaluation and human health guarding. However, conventional strategies for realizing reliable,...

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Rapid identification and analysis of pesticide residue on real-world sample by a portable platform is of growing interest for monitoring food safety and safeguarding human health. Herein, we developed a robust surface-enhanced Raman spectroscopy (SERS) sensor based on ZrO 2 @TiO 2 /Ag substrate for the analysis of pesticide residues. The synergetic effects of the metal organic framework (MOF)-derived porous ZrO 2 @TiO 2 heterostructure induced charge transfer enhancement and the electromagnetic enhancement from the plasmonic silver nanoparticles (AgNPs) hotspot generate significant SERS enhancement signal. The SERS substrate exhibits superior long-term stability and signal homogeneity for SERS quantitative analysis. The platform has the capability to detect not only model molecule of 4-ATP but also pesticides of triazophos and fonofos at the extremely low concentration of 10 À8 M. Moreover, we simulate the quantitative detection of pesticide residue on real objects by spraying pesticides on dendrobium and chrysanthemum leaves, followed by transferring to the SERS platform to perform analysis. The nearly linear fitting curve with a wide concentration range suggests the superior qualitative detection capability.Remarkably, two components and three components of the pesticides are readily identified in a rapid way. The approach provides the rapid analysis, lowcost device, and portable and quantitative pesticide identification and offers a clear path to multicomponent analysis at a trace level. K E Y W O R D Sidentification and quantification, metal organic frames, rapid pesticide analysis, surfaceenhanced Raman spectroscopy (SERS), ZrO 2 @TiO 2 heterojunction

Figure 6. SERS spectra collected from different concentrations of a) triazophos and d) diquat of honeysuckle leaves using our SERS platform. b,e) Corresponding linear relationship between Raman intensity and detected concentrations. SERS spectra of c) three components and f) four components.