Related Experiment Video
Updated: Sep 21, 2025

Colorimetric Paper-based Detection of Escherichia coli, Salmonella spp., and Listeria monocytogenes from Large Volumes of Agricultural Water
Published on: June 9, 2014
Engineering of 2D artificial nanozyme-based blocking effect-triggered colorimetric sensor for onsite visual assay of
Yizhong Shen1,2, Yunlong Wei3, Zhenmin Liu4
1State Key Laboratory of Dairy Biotechnology, Shanghai Engineering Research Center of Dairy Biotechnology, Dairy Research Institute, Bright Dairy & Food Co., Ltd, Shanghai, 200436, China. yzshen@hfut.edu.cn.
Abstract:
Accurate and low-cost onsite assay of residual antibiotics in food and agriculture-related matrixes (e.g., milk) is of significant importance for evaluating and controlling food pollution risk. Herein, we employed hybrid Cu-doped-g-C3N4 nanozyme to engineer smartphone-assisted onsite visual sensor for reliable and precise reporting the levels of tetracycline (TC) residues in milk through π-π stacking-triggered blocking effect. Benefiting from the synergetic effects of Cu2+ and g-C3N4 nanosheet, Cu-doped-g-C3N4 nanocomposite exhibited an improved peroxidase-like activity, which could effectively catalyze H2O2 to oxidate colorless TMB into steel-blue product oxTMB. Interestingly, owing to the blocking effect caused by the π-π stacking interaction between TC tetraphenyl skeleton and Cu-doped-g-C3N4 nanozyme, the affinity of Cu-doped-g-C3N4 nanocomposite toward the catalytic substrates was remarkably blocked, resulting in a TC concentration-dependent fading of solution color. Using smartphone-assisted detection a simple, low-cost, reliable, and sensitive portable colorimetric sensor-based nanozyme for onsite visual monitoring the residual TC in milk was successfully developed with a detection limit of 86.27 nM. Of particular mention is that this detection limit is comparable to most other reported colorimetric methods and below most official allowable residue thresholds in milk matrixes. This work gave a novel insight to integrate two-dimensional (2D) artificial nanozymes-based π-π stacking-triggered blocking effect with smartphone-assisted detection for developing efficient and low-cost colorimetric point-of-care testing of the risk factors in food and agriculture-related matrixes.

