Issue 5, 2026

A quantitative identification fluorescent probe for highly selective detection of Cu2+ in food and environmental samples

Abstract

The potential accumulation of copper ions (Cu2+) in the food chain poses significant risks, making it imperative to develop efficient tools for real-time monitoring of Cu2+ levels in food, plants, and biological systems. In this study, two novel fluorescent probes, RC-1 and RC-2, were synthesized using triphenylamine derivatives through a condensation reaction for the detection of Cu2+. Among the two probes, probe RC-2, which contains 4-aminobenzamide, exhibited excellent selectivity, ultra-fast response (<30 s), a low detection limit of 26.8 nM, high water solubility, and ease of synthesis. Probe RC-2 demonstrated effective quantitative monitoring of Cu2+ in various food and water samples. The analytical performance showed satisfactory accuracy (80.0–118.9%) and good precision, as evidenced by relative standard deviation (RSD) values below 10%. The accuracy of the method was further substantiated via inductively coupled plasma mass spectrometry (ICP-MS). A Mini Program based on WeChat was designed for Cu2+ quantification in food samples, simultaneously enhancing public awareness of food safety. This study highlighted the significant potential of integrating smartphones with fluorescent probes for enhanced monitoring of food safety. Finally, RC-2 was successfully applied for imaging Cu2+ in HeLa cells and plant tissues, highlighting its potential for selective detection of Cu2+ in complex matrices.

Graphical abstract: A quantitative identification fluorescent probe for highly selective detection of Cu2+ in food and environmental samples

Supplementary files

Article information

Article type
Paper
Submitted
22 Oct 2025
Accepted
11 Dec 2025
First published
23 Jan 2026

Anal. Methods, 2026,18, 1092-1100

A quantitative identification fluorescent probe for highly selective detection of Cu2+ in food and environmental samples

H. Xu, J. Zhang, X. Ren, Y. Zhang, Y. Yang, X. Zhou, W. Yang, M. Xie, J. Yang, X. Wang, Z. Yuan and J. Liu, Anal. Methods, 2026, 18, 1092 DOI: 10.1039/D5AY01763G

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