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Updated: Jul 12, 2026
ELIME (Enzyme Linked Immuno Magnetic Electrochemical) Method for Mycotoxin Detection
Published on: October 23, 2009
Machine learning-assisted Mn-N-C nanozyme colorimetric sensor array for trace-level detection of biogenic amines in
Jiajie Li1, Changlong Dai1, Shuyu Li1
1Zhejiang Provincial Collaborative Innovation Center of Agricultural Biological Resources Biochemical Manufacturing, Zhejiang University of Science and Technology, Hangzhou 310023, Zhejiang, China; Zhejiang-Spain Joint Laboratory of Oil and Protein Nutrition and Health, Zhejiang University of Science and Technology, Hangzhou 310023, Zhejiang, China.
A novel nanozyme sensor accurately detects biogenic amines (BAs) in meat using dual enzyme-like activity. This breakthrough enables early warning for food quality deterioration, enhancing safety.
Area of Science:
- Analytical Chemistry
- Materials Science
- Biotechnology
Background:
- Accurate biogenic amine (BA) detection in meat is difficult due to structural similarities and co-occurrence.
- Developing sensitive and selective methods for BA monitoring is crucial for food safety and quality control.
Purpose of the Study:
- To synthesize a nanozyme with dual oxidase (OXD) and peroxidase (POD)-like activities for biogenic amine detection.
- To develop a colorimetric sensor array coupled with an artificial neural network for accurate BA identification in meat.
- To establish a reliable system for early-stage monitoring of food quality deterioration.
Main Methods:
- Synthesis of an Mn-N-C nanozyme via metal-organic framework confined pyrolysis.
- Construction of a colorimetric sensor array utilizing the nanozyme's dual enzyme-like activities.
- Development of a concentration-independent recognition model using an artificial neural network.
Main Results:
- The Mn-N-C nanozyme exhibited excellent OXD and POD activities with low Km values (0.1584 mM and 0.1498 mM, respectively).
- The colorimetric sensor array achieved 100% classification accuracy for four representative BAs (2-10 ppm).
- The integrated system accurately identified trace-level BAs in fish, pork, and chicken, demonstrating robustness against signal nonlinearity.
Conclusions:
- The developed Mn-N-C nanozyme-based sensor offers a sensitive and selective platform for biogenic amine detection in meat.
- The artificial neural network model effectively addresses signal nonlinearity, enabling reliable quantification.
- This integrated system provides a promising tool for early warning of food quality deterioration during storage and transportation.
