Food adulteration is a global concern that is a significant public health risk. Such issues demand sophisticated analytical devices with high-speed sensitivity toward detecting adulterants. The surface enhanced Raman spectroscopic (SERS) technique is an advanced tool that gains wide appreciation due to its very high sensitivity and selectivity. Being an excellent ultra-trace contaminant-detecting tool even within complex food matrices, this resource becomes fundamental in food safety protection. SERS is found to detect trace concentrations of synthetic dyes. Recent advancements have been made on new substrates that enhance signal stability among noble metals, hybrid nanostructures, and metal-organic frameworks (MOFs). These substrates are further functionalized with specific chemical moieties to improve the selectivity and reduce the matrix interference. SERS, combined with advanced computing tools like machine learning and chemometric algorithms, has completely changed the data analysis scenario; nowadays, high-throughput simultaneous detection and accurate adulterant quantification are possible. With rapid outputs and less sample preparation, portable SERS devices revealed promise in on-site food safety monitoring. Subsequent developments that address several fundamental concerns regarding cost, reusability, and scalability ultimately make SERS devices more widely adaptable. This chapter covers the emerging aspects of SERS substrates, enhancement strategies, and computational improvements concerning synthetic dye detection. It speaks of the potential of SERS as a flexible tool for ensuring public health and food safety worldwide while discussing the challenges and opportunities in developing inexpensive, reusable substrates.