Ensuring food safety using fluorescent nanoparticles-based immunochromatographic test strips

Immunochromatographic test strip (ICTS) has become one of the most widely used rapid diagnostics platforms for the point-of-care testing of various contaminant residues in food. However, traditional gold nanoparticle (AuNP)-based ICTSs suffer limited sensitivity ranged from ng/mL to μg/mL, thus severely hindering them from meeting the increasing demand for trace target detection. The use of novel nanomaterials with high signal strength to replace AuNPs as signal probes is considered as the most effective strategy to enhance the sensitivity of ICTS nanosensor. Among them, highly luminescent nanomaterials have attracted increasing interest in improving the detection performance of ICTS due to its advantages of visualization, quantitation, multiplexing, anti-jamming capability, and high sensitivity. Currently available nanomaterials include dye-based fluorescent nanomaterials, semiconductor quantum dots and its nanobeads, up-conversion nanoparticles, time-resolved fluorescence nanomaterials, aggregation-induced emission nanomaterials, noble metal nanoclusters, and magnetic fluorescent nanomaterials, and they have been successfully applied for detecting various hazardous substances, including pesticide and veterinary drug residues, food additives, mycotoxins, heavy metal ions, allergens, and microorganisms. In this review, thus we comprehensively summarize the application potentials and critical roles of such nanomaterials as signal reporters in current ICTS systems to ensure food safety. A detailed classification of signal probes with emphasis on the inherent advantage, synthesis, signal amplification strategy, and further improvement of each luminescent nanomaterial was discussed and the state-of-the-art of commercial fluorescent ICTS kits and readers for food safety was summarized. Further improvement should focus on the design and development of high-quality luminescent nanomaterials, ultra-sensitive detection, multiplexing and multimode sensing, accurate quantification, and intelligent signal reading.