Rapid Detection of Deoxynivalenol in Cereals Based on Amplified Luminescence Proximity Homogeneous Detection Technology

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.

Authors

Institutions

Publication Details

Journal
Archiv für Lebensmittelhygiene
Published
2025-10-24
DOI
https://doi.org/10.31083/jfsfq42752
Citations
1
Primary Topic
Mycotoxins in Agriculture and Food
Type
article
Field-Weighted Citation Impact
1.75

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Rapid Detection of Deoxynivalenol in Cereals Based on Amplified Luminescence Proximity Homogeneous Detection Technology

Dian Li, Xiumei Zhou, Biao Huang, Yuan Qin et al.
1 citations
Archiv für Lebensmittelhygiene
Mycotoxins in Agriculture and Food
1.75
article

Rapid Detection of Deoxynivalenol in Cereals Based on Amplified Luminescence Proximity Homogeneous Detection Technology

Dian Li, Xiumei Zhou, Biao Huang, Yuan Qin, Nenghua Zhang, Jie Chen, Tianyu Zheng, S. C. Kao, Chongling Yan
article en
1 citations

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.

Archiv für LebensmittelhygieneVol. 76(4)
Zhejiang Chinese Medical University (CN), Zhejiang Sci-Tech University (CN), Suzhou University of Technology (CN), Jiaxing University (CN), First Hospital of Jiaxing (CN)
Zhejiang Chinese Medical University
Openalex Percentile: Top 11%
Mycotoxins in Agriculture and Food
1.75
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.