On-site AFB1 detection in food via dual-gated system and Zn2+-doped UCNPs embedded in injectable PGB hydrogel

An injectable BZUCNPs-PACMSNs/PGB sensor was proposed to detect AFB 1 . • BPEI was coated on ZUCNPs to improve the water-soluble ability of ZUCNPs • A dual-gated strategy was presented to improve the stability of UCNPs sensor. • BPEI@Cu 2+ can effectively quench the fluorescence of ZUCNPs due to IFE. • Injectable PGB hydrogel was utilized for stable and on-site AFB 1 detection. An expanding presence of aflatoxin B 1 (AFB 1 ) contamination across the global food supply represents a serious threat to public health. This work developed a portable sensor using Zn 2+ -doped upconversion nanoparticles (ZUCNPs) that Cu 2+ -induced fluorescence quenching with an injectable polyvinyl alcohol/gelatin/borax (PGB) hydrogel. First, ZUCNPs exhibiting enhanced fluorescence were modified with branched polyethylenimine (BPEI) to form signal probes known as BZUCNPs. Additionally, mesoporous silica nanoparticles (MSNs) were fabricated via sol-gel methods, loaded with Cu 2+ and coated with aptamer (Apt) and polydopamine (PDA) to create dual-gated capture probes (PACMSNs). Afterwards, BZUCNPs and PACMSNs were mixed to form sensing probes and then integrated into the PGB hydrogel, forming the final sensor (BZUCNPs-PACMSNs/PGB). In the presence of AFB 1 at pH 5.5, the AFB 1 diffused into the PGB hydrogel, disrupting the PDA and Apt layer due to acid environment and changing the structure of Apt as AFB 1 specifically bound to it. Then, Cu 2+ released and facilitated the formation of BPEI@Cu 2+ complex on the surface of ZUCNPs, which produced inner filter effect (IFE) that quenched fluorescence. When experimental conditions were optimized, a pronounced linear calibration curve ( R 2  = 0.994) was observed, linking fluorescence to the logarithm of AFB 1 levels across a 0.1–100 μg/kg AFB 1 range. And its sensitivity was characterized with a detection limit of 0.03 μg/kg. Furthermore, the sensor's applicability was confirmed through analysis of food matrices, including wheat, corn, peanuts, and water, yielding high analytical accuracy with relative standard deviations below 6.08% and recovery rates ranging from 93.77% to 107.67%.