Electrochemical Biosensors for Rapid Detection of Pesticide Residues in Fresh Produce: A Review of Nanomaterial-Enhanced Platforms

Abstract

Pesticides residues in fresh produce is an important food safety issue as repeated exposure through the diet can cause neurological, reproductive, endocrine, developmental and carcinogenic effects. Traditional chromatographic techniques are reliable for the identification and quantification of pesticides, but they are costly, need specialized staff, labor-intensive sample preparation and centralized laboratory. The present review explores the electrochemical biosensors based on nanomaterials as rapid, sensitive, portable and cost-effective alternatives for pesticide-residue screening. Metal nanoparticles, metal oxides, carbon nanomaterials, conducting polymers, metal–organic frameworks, two-dimensional materials and hybrid nanocomposites enhance the conductivity of the electrodes, surface area, immobilization of bioreceptors, catalytic activity, and signal amplification. Critically discussed are enzyme-based biosensors, immunosensors, aptamer-based sensors, molecularly imprinted polymer sensors and non-enzymatic platforms developed for organophosphates, carbamates, organochlorines, pyrethroids and neonicotinoids. Sample preparation, matrix effects, electrode fouling, sensitivity, selectivity, detection limits, recovery, reproducibility and comparison with chromatographic reference methods are also assessed in the review. Decentralized monitoring might be possible with emerging screen-printed electrodes, paper-based devices, microfluidic systems, smartphone interfaces, connectivity to the Internet of Things, and artificial intelligence-assisted signal analysis. Yet, there are significant challenges towards stability and safety of sensors, reproducible manufacture of nanomaterials, multiplexing, regulatory validation, and commercialization. To realize these platforms into reliable food-safety tools, standardized fabrication, use of sustainable materials, real-sample validation, and interlaboratory evaluation are key.