2026/07/26 by Muhammad Usman, Rana Morsi, Dina Ashraf +2
Chemistry · Materials Science · #Analytical Chemistry and Chromatography #Analytical chemistry methods development #Covalent Organic Framework Applications
paper · doi:10.1016/j.jfca.2026.109401
openalex publication_date 2026/07/26 · openalex created_date 2026/07/27 · openalex updated_date 2026/07/30
Pesticide residues in food commodities pose significant risks to public health, necessitating sensitive, selective, and reliable analytical methods for regulatory compliance. Conventional sample preparation techniques, including liquid–liquid extraction (LLE), solid-phase extraction (SPE), and QuEChERS, remain widely used but are often limited by high solvent consumption, matrix interferences, limited selectivity, and poor reusability in complex food matrices. Covalent organic frameworks (COFs), owing to their crystalline porous architectures, tunable pore chemistry, and high surface areas, have emerged as promising materials for selective pesticide extraction and detection. This review critically evaluates advances reported between 2019 and 2025 in COF-based platforms for the extraction and detection of organophosphorus, organochlorine, neonicotinoid, carbamate, pyrethroid, triazine, and phenylurea pesticides in food matrices. Recent developments in COF-based SPE, magnetic SPE (MSPE), solid-phase microextraction (SPME), and sensing platforms, including colorimetric, fluorescence, luminescence, electrochemical, and surface-enhanced Raman scattering (SERS) methods, are critically assessed with emphasis on analytical performance, adsorption mechanisms, matrix compatibility, and compliance with European Union maximum residue limits. Unlike previous reviews emphasizing environmental applications, this review focuses on food matrices, including vegetables, fruits, cereals, dairy products, beverages, and poultry, while systematically comparing COF-based methods with conventional extraction techniques in terms of recovery, matrix effects, adsorption capacity, and reusability. Current challenges, including synthesis complexity, cost, limited validation in meat and fermented food matrices, and insufficient long-term stability under realistic food conditions, are discussed. Future perspectives highlight greener COF synthesis, advanced framework engineering, portable sensing platforms, artificial intelligence-assisted data analysis, and integration with routine LC–MS/MS workflows for practical food safety monitoring.