Enhanced illumination of Aflatoxin B₁ by N-bromosuccinimide integrated with quantum dots: A ratiometric fluorescence...

Aflatoxin B₁ (AFB₁) is one of the most potent mycotoxins, posing serious health risks even at trace concentrations. Thus, developing rapid and in situ analytical strategies is essential for food safety monitoring. Unlike previously reported complex and costly methods, simple derivatization assay to enhance the intrinsic fluorescence of AFB₁ has emerged as a highly attractive strategy for direct detection.

The reaction of AFB₁ with N-bromosuccinimide (NBS) affords a highly fluorescent derivative, characterized by a distinct emission peak at 435 nm. This fluorescence intensity increases proportionally with AFB₁ concentration. To enhance visual discrimination, a ratiometric fluorescent probe was designed using mercaptopropionic acid-capped cadmium telluride quantum dots (CdTe@MPA QDs) as a reference fluorophore, providing stable red emission at 660 nm. The ratiometric signal, generated from the enhanced blue emission of the AFB₁ derivative and the constant red emission of CdTe@MPA QDs, enables accurate quantification over 0.5-75.0 ng mL^-1 with a detection limit of 0.10 ng mL^-1 within 15 min. In addition to quantitative analysis, the assay provides a vivid, concentration-dependent colorimetric transition from red to blue (via pink and purple). This distinct visual readout enables rapid, in situ screening of AFB₁ in food samples.The probe exhibits good selectivity toward AFB₁, and multivariate analysis using Principal Component Analysis-Linear Discriminant Analysis (PCA-LDA) further validates the robustness and discrimination capability of the proposed ratiometric platform. The practicability and applicability of the probe were successfully validated in corn and edible oil samples.

This study presents a facile derivatization method designed to enhance the fluorescence emission of AFB₁, thereby enabling direct visual detection. Compared to conventional chromatographic systems utilizing Kobra Cell derivatization, the proposed approach is significantly more streamlined, rapid, and cost-effective, while maintaining highly competitive sensitivity and accuracy.