Abstract:
The present study investigates the development and validation of a novel paper-based biosensor
for the detection of antibiotic residues, specifically tetracycline, in milk, which is crucial for
ensuring quality control in the dairy sector, a key component of agribusiness management. The
effective management of antibiotic residues is vital not only for public health but also for
maintaining consumer trust and compliance with international safety standards, which directly
impacts the sustainability and profitability of the dairy industry. The increasing prevalence of
antibiotic residues in dairy products, due to the overuse and misuse of antibiotics in livestock,
poses significant public health risks, including the development of antibiotic-resistant bacteria. To
address this challenge, a cost-effective, portable, and environmentally friendly sensor was
designed using Whatman filter paper and a Metal-Organic Framework (Cu-MOF) with peroxidase like activity. The sensor operates on a colorimetric principle, where the presence of tetracycline
inhibits the oxidation of tetramethylbenzidine (TMB) by hydrogen peroxide, resulting in a
quantifiable color change.
The Cu-MOF was synthesized and characterized using Scanning Electron Microscopy (SEM), X ray Diffraction (XRD), and Fourier Transform Infrared Spectroscopy (FTIR), confirming its
successful formation and appropriate chemical structure. The sensor's sensitivity was tested across
a range of tetracycline concentrations, achieving a detection limit of 0.1 µM, which is comparable
to existing detection methods. The paper-based device demonstrated excellent stability over time
and maintained its functionality under various storage conditions.
This research highlights the potential of the developed sensor as a reliable tool for on-site detection
of antibiotic residues in milk, contributing to food safety and public health. The sensor's ease of
use, low cost, and effectiveness make it suitable for deployment in resource-limited settings,
offering a practical solution to the widespread issue of antibiotic contamination in dairy products.
Future work will focus on expanding the sensor's capabilities to detect other antibiotic classes and
integrating a mobile application for real-time data analysis. This innovation not only ensures
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consumer safety but also supports the agribusiness sector in maintaining high standards of product
quality and market competitiveness.