Medicinal and edible homologs (MEHs) offer significant preventive and therapeutic benefits for various diseases and health functions. However, the widespread application of MEHs faces significant challenges, particularly in quality control and rapid identification. In this study, we present a novel approach that combines surface-enhanced Raman spectroscopy (SERS) based on spectral set, referred as "SERSome", with deep learning to develop an identification model for analyzing MEHs. The platform uses silver nanoparticles prepared via reduction with NaBH