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Updated: May 12, 2026

Colorimetric Paper-based Detection of Escherichia coli, Salmonella spp., and Listeria monocytogenes from Large Volumes of Agricultural Water
Published on: June 9, 2014
Integrated and confinable paper-based chip biosensor for all-in-one colorimetric detection of aflatoxin B1
Sareh Sadat Moshirian-Farahi1, Hamidreza Rahmanian2, Jianxiong Wu3
1College of Biosystems Engineering and Food Science, Zhejiang Key Laboratory of Intelligent Sensing and Robotics for Agriculture, Zhejiang University, Hangzhou, 310058, China; Qingyuan County Sanheyuan Agriculture Development Co. ltd., Qingyuan, China.
None:
This study presents the development of a rapid and highly sensitive colorimetric biosensor for the detection of aflatoxin B1 (AFB1), utilizing a peroxidase-mimetic nanozyme in combination with a membrane-confined signal amplification strategy. The biosensor platform incorporates AFB1-specific aptamer-labeled Fe3+-doped mesoporous carbon nanospheres, which hybridize with a complementary strand immobilized on paper nanofibers. Upon binding with AFB1, the nanozyme detaches and is subsequently removed through a washing step. The remaining nanozyme catalyzes the oxidation of 3,3',5,5'-tetramethylbenzidine in the presence of H2O2, generating a blue-colored signal. To facilitate real-time, quantitative signal analysis, a smartphone-based imaging strategy is employed. In contrast to conventional open-solution detection methods, this approach confines the catalytic reaction and its products within the membrane, thereby enhancing the signal intensity. The integration of the nanozyme's high catalytic efficiency with the signal amplification enabled by membrane confinement results in superior sensitivity, stability, and operational simplicity. The biosensor demonstrates a broad detection range from 0.01 to 1000 ng mL-1 and an exceptionally low detection limit of 3.9 pg mL-1, outperforming most analogous systems. Additionally, the biosensor exhibits excellent performance in complex sample matrices, such as chicken feed and traditional Chinese medicinal herbs. Through the combination of smartphone imaging for quantitative analysis and rapid, visual detection, this platform provides a versatile, user-friendly tool for real-time, on-site food safety monitoring and health surveillance.
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