AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Home Food Science Article
PDF (3.1 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Publishing Language: Chinese | Open Access

Fe3O4 Nanoparticle-Enhanced Laccase-Copper Hybrid Nanoflower-Based Enzyme Sensor for Rapid Determination of Polyphenols in Foods

Mengmeng GUO Hang LUDingxin CHANGFan YUShuguo LI ( )
College of Food Science and Biology, Hebei University of Science and Technology, Shijiazhuang 050018, China
Show Author Information

Abstract

A novel biosensor, Lac-Cu/Fe3O4/MWCNTs-COOH/GCE, was prepared for the rapid and sensitive determination of polyphenols in foods by immobilizing magnetic nanosized ferric oxide (Fe3O4), carboxylated multi-wall carbon nanotubes (MWCNTs-COOH) and laccase-Cu (Lac-Cu) onto the surface of a glassy carbon electrode (GCE). The morphological structure of the modified material was characterized by scanning electron microscopy (SEM). This nanoenzyme sensor was characterized by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The CV results showed that the oxidation peak current (Ip) of gallic acid at GCE, Lac-Cu/GCE, Lac-Cu/MWCNTs-COOH/GCE and Lac-Cu/Fe3O4/MWCNTs-COOH/GCE was 19.38, 38.87, 46.61 and 59.95 μA, respectively, indicating that the biosensors of Fe3O4/MWCNTs-COOH and Lac-Cu had a significant catalytic effect on the electrochemical oxidation of gallic acid, the oxidation peak current increased by 2.10 times compared to the glassy carbon electrode. The experimental conditions optimized by linear sweep voltammetry (LSV) were as follows: 0.1 mol/L citric acid at pH 3 as the electrolyte solution, 4:1 of MWCNTs-COOH to Fe3O4 ratio, 5 μL of the composite solution, 4 U of Lac-Cu hybrid nanoflowers, and 12 min of enrichment time. Under these conditions, the Ip exhibited a linear relationship with polyphenol concentration (Cpp) over the range of 7 to 118 μmol/L, described by the equation Ip = 0.6797 Cpp + 38.978 (R2 = 0.9993). The limit of detection (LOD) was 1.5 × 10-9 mol/L (signal-to-noise ratio, RSN = 3). For the detection of oat polyphenols, this method outperformed the Folin phenol method in accuracy, with spiked recovery rates of 94.45% to 103.5%. With its advantages of rapidity, high accuracy, low LOD and good interference resistance, this method is practical for the rapid and sensitive determination of polyphenols in foods.

CLC number: TS207.3 Document code: A Article ID: 1002-6630(2025)19-0195-10

References

【1】
【1】
 
 
Food Science
Pages 195-204

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
GUO M, LU H, CHANG D, et al. Fe3O4 Nanoparticle-Enhanced Laccase-Copper Hybrid Nanoflower-Based Enzyme Sensor for Rapid Determination of Polyphenols in Foods. Food Science, 2025, 46(19): 195-204. https://doi.org/10.7506/spkx1002-6630-20250324-180

132

Views

1

Downloads

0

Crossref

0

Scopus

0

CSCD

Received: 24 March 2025
Published: 15 October 2025
© Beijing Academy of Food Sciences 2025.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).