Surface-enhanced Raman scattering (SERS) has gained substantial interest for the practical analysis of trace amounts of various molecules. However, improving the magnitude of the electromagnetic enhancement and preparing the substrate for long-term use remains top research priorities. This study presents a novel and straightforward synthesis method for zinc oxide nanorices (ZnONRs) decorated with small silver particles (Ag/ZnONR), which can serve as a highly stable, sensitive, and reproducible material for SERS detection of isoprocarb (IPC) and crystal violet (CV). Integrating ZnONR and AgNPs at an appropriate mixing ratio can generate many plasmonic 'hotspots' on the surface due to the strong surface plasmon capability of AgNPs when excited by appropriate light. The length of ZnO nanorods (ZnONR) has been controlled to range from 100 nm to 120 nm, with an aspect ratio (AR, the ratio of nanoparticle length to width) of about 3:1. Additionally, the formed silver nanoparticles have an average diameter of approximately 20–40 nm and randomly distributed on the surface of the ZnO. Specifically, we found that the exceptional detection enhancement factor was 2.5 × 109, along with high reproducibility due to the embedding of AgNPs in the inert structure of ZnO nano rice, which helps prevent the loss of AgNPs during analysis and can be reused multiple times while maintaining good signal intensity stability. Significantly, this embedded nanostructure could achieve a reasonable limit of detection of 0.402 nM for CV and 0.147 pM for IPC, with a high reproducibility (RSD of 5,98%). The electromagnetic field enhancement phenomenon of this nanomaterial was further analyzed through Finite-Difference Time-Domain simulations, demonstrating that the intensity of the electromagnetic field (EM-field) of Ag/ZnONRs (66.0) is significantly ten times greater than that observed with pristine AgNPs (6.31) or ZnONRs (1.84). Integrating these nanomaterials creates a sophisticated category of hybrid nanosubstrates suitable for a wide range of future detection applications employing the SERS method.