Rapid Detection of Deoxynivalenol in Cereals Based on Amplified Luminescence Proximity Homogeneous Detection Technology
Year: 2025
Type: article
Abstract: Background: To address challenges of low sensitivity, complex operation, and matrix interference in detecting deoxynivalenol (DON) in cereals, this study developed a novel wash-free detection system using amplified luminescence proximity homogeneous assay (AlphaLICA) technology. Methods: The method leverages energy transfer between microspheres and antigen-antibody interactions: DON antibodies competitively bind to DON-BSA-luminescent microspheres and DON standards/samples, with bound antibodies detected via goat anti-mouse IgG-conjugated photosensitive microspheres. Results: Results demonstrated a detection limit (LOD) of 1.03 ng/mL and quantitation limit (LOQ) of 7.57 ng/mL. Intra-/inter-batch coefficients of variation were <6.13% and 6.67%, respectively. Recovery rates in wheat, corn, and rice reached 97.52%–105.83% (relative standard deviation (RSD) ≤12.83%), with <0.21% cross-reactivity to aflatoxin B1. Compared to enzyme-linked immunosorbent assay (ELISA), AlphaLICA showed superior sensitivity (1.03 vs. 10 ng/mL), faster detection (5 vs. 35 min), broader linear range (7.57–800 vs. 12.5–200 ng/mL), and lower variability (6.13%/6.67% vs. 8%/12%). Pearson correlation analysis confirmed a strong association with ELISA results (p < 0.001, r = 0.8374). Conclusions: The established DON-AlphaLICA method provides a simple, rapid, sensitive, and accurate solution for DON detection, effectively addressing current limitations in grain safety monitoring. This innovative method enables efficient screening of mycotoxin contamination in agricultural products while minimizing procedural complexity.
Source: Archiv für Lebensmittelhygiene
DOI: 10.31083/jfsfq42752
Authors: Dian Li, Jie Chen, Shangbin Kao, Canlong Yan, Tianyu Zheng, Yuan Qin, Xiumei Zhou, Nenghua Zhang, Biao Huang
Language: English
Subfield: Plant Science
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W4415995732
