Machine learning intelligently selects feature values to construct a sensor array based on tri-functional Mn-doped covalent organic polymer nanozymes for identifying flavonoid compounds

Herein, a novel tri-functional Mn-doped covalent organic polymer nanozyme (Mn-COP) with peroxidase-like, oxidase-like, and laccase-like activities was synthesized. The strong reducing power of flavonoids inhibited the tri-enzymes-like activity from Mn-COP, with the trend increasing as a function of...

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Published in:Food chemistry Vol. 496; no. Pt 2; p. 146792
Main Authors: Zhang, Guo-Qi, Jiang, Wen-Cai, Li, Xiao-Mei, Li, Ren-Jie, Feng, Yi, Nai, Ri-Ge Li, Cheng, Hui-Lin, Hou, Zhi-Bo, Luo, Xiao-Jun, Zhao, Yan
Format: Journal Article
Language:English
Published: England Elsevier Ltd 25.12.2025
Subjects:
Biosensing Techniques - instrumentation
Biosensing Techniques - methods
Flavonoids
Flavonoids - analysis
Flavonoids - chemistry
Machine Learning
Manganese - chemistry
Nanostructures - chemistry
Nanozyme
Polymers - chemistry
Random Forest algorithms
Sensor array
Nanozyme
Random Forest algorithms
Flavonoids
Sensor array
ISSN:0308-8146, 1873-7072, 1873-7072
Online Access:Get full text
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Summary:Herein, a novel tri-functional Mn-doped covalent organic polymer nanozyme (Mn-COP) with peroxidase-like, oxidase-like, and laccase-like activities was synthesized. The strong reducing power of flavonoids inhibited the tri-enzymes-like activity from Mn-COP, with the trend increasing as a function of reaction time. The Mn-COP endowed the sensor array with improved accuracy due to three different chemical reactions used as recognition channels. To assess the significance of reaction time in optimizing eigenvalues, the Random Forest algorithm (RF) was employed. The nanozyme sensor array effectively distinguished various flavonoids. The incorporation of the RF enabled accurate identification and prediction of 7 flavonoids within the concentration range of 10–500 μM present in a variety of traditional Chinese medicines. Overall, a key innovations of this work is the introduction of a more scientific and intelligent approach to selecting feature values, thereby opening a promising avenue for the development of sophisticated nanozyme sensor arrays. •Optimize the eigenvalues of the nanozyme sensor array using machine learning algorithms.•A tri-enzyme-like activies exhibited by Mn-COP was successfully synthesized.•An array of colorimetric sensors for identifying flavonoids was constructed.
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ISSN:0308-8146
1873-7072
1873-7072
DOI:10.1016/j.foodchem.2025.146792