Dual-Mode Colorimetric/SERS Lateral Flow Immunoassay with Machine Learning-Driven Optimization for Ultrasensitive Mycotoxin Detection.

Journal: Analytical chemistry
PMID: 39951511

Abstract

Detecting and quantifying mycotoxins using LFIA are challenging due to the need for high sensitivity and accuracy. To address this, a dual-mode colorimetric-SERS LFIA was developed for detecting deoxynivalenol (DON). Rhodium nanocores provided strong plasmonic properties as the SERS substrate, while silver nanoparticles created electromagnetic "hotspots" to enhance signal sensitivity. Finite element modeling optimized the electromagnetic field intensity, and Prussian blue generated a distinct signal at 2156 cm, effectively reducing background interference. This dual-mode LFIA achieved a detection limit of 4.21 pg/mL, 37 times lower than that of colloidal gold-based LFIA (0.156 ng/mL). Machine learning algorithms, including ANN and KNN, enabled precise classification and quantification of contamination, achieving 98.8% classification accuracy and an MSE of 0.57. These results underscore the platform's potential for analyzing harmful substances in complex matrices and demonstrate the important role of machine learning-enhanced nanosensors in advancing detection technologies.

Authors

  • Boyang Sun
    School of Emergency Management & Safety Engineering, China University of Mining and Technology, Beijing, 100083, China.
  • Haiyu Wu
    College of Food Science and Engineering, Northwest A&F University, Yangling 712100, Shaanxi, China.
  • Tianrui Fang
    College of Food Science and Engineering, Northwest A&F University, Yangling 712100, Shaanxi, China.
  • Zihan Wang
    Graduate School, Beijing University of Chinese Medicine, Beijing, China.
  • Ke Xu
    Mechatronics Engineering of University of Electronic Science and Technology of China, Chengdu, 611731, China.
  • Huiqi Yan
    College of Food Science and Engineering, Northwest A&F University, Yangling 712100, Shaanxi, China.
  • Jinbo Cao
    College of Food Science and Engineering, Northwest A&F University, Yangling 712100, Shaanxi, China.
  • Ying Wang
    Key Laboratory of Macromolecular Science of Shaanxi Province, School of Chemistry & Chemical Engineering, Shaanxi Normal University, Xi'an, Shaanxi 710062, China.
  • Li Wang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.

Keywords

External Resources

Popular Topics
Recent Journals