Key points are not available for this paper at this time.
Metal-organic frameworks (MOFs) have r–evolutionized electrochemical sensing of food additives through their tunable porosity, high surface area, and versatile functionalities. Compared to conventional techniques like HPLC, which require sophisticated laboratory setups and costly reagents, MOF-based sensors offer a portable, rapid, and cost-effective alternative for detecting nitrites, preservatives, and pesticides. However, initial MOF designs such as MIL-101-struggled with poor conductivity and structural instability, limiting their practical use. Recent enhancements integrating carbon nanomaterials, enzymes, hydrogels, and biomolecules have significantly improved the sensitivity, selectivity, and robustness of MOF-based platforms. Furthermore, Optimization Across Food Matrices is now being leveraged to refine MOF design, optimizing stability and selectivity across complex food matrices and accelerating the pathway to real-time food safety monitoring. Despite persistent challenges in reproducibility, long-term durability under harsh conditions, and scalability for commercial implementation, MOFs continue to evolve as promising tools for accessible and efficient food additive analysis.
Venkatesan et al. (2025) studied this question.