New Electrochemical Sensor Enhances Detection of Antibiotic Residues in Food

Researchers have introduced a novel method for detecting ciprofloxacin (CIP) in food products using a self-enhanced near-infrared electrochemiluminescence (ECL) probe. Detailed in a recent Foods study, this approach leverages functionalized copper nanowires (CuNWs) to improve sensitivity and specificity in monitoring antibiotic residues, addressing key food safety concerns.

Study: Self-Enhanced Near-Infrared Copper Nanoscale Electrochemiluminescence Probe for the Sensitive Detection of Ciprofloxacin in Foods. Image Credit: nevodka/Shutterstock.com

Background

Ciprofloxacin, a widely used fluoroquinolone antibiotic, plays a crucial role in treating bacterial infections in livestock, particularly pigs and poultry. However, with a metabolic conversion rate of less than 30 %, a substantial amount of unmetabolized CIP enters the environment and food chain. This raises serious food safety concerns, as antibiotic residues can pose health risks and contribute to antibiotic resistance. The need for efficient, reliable detection methods has never been more pressing.

Traditional detection techniques such as high-performance liquid chromatography (HPLC), liquid chromatography-mass spectrometry (LC-MS), and Raman spectroscopy are effective but often costly and complex. These limitations highlight the demand for more accessible and robust alternatives.

The Study

This study presents a molecularly imprinted electrochemiluminescent sensor (MIECLS) constructed with CuNWs modified with polyvinylpyrrolidone (PVP). Functionalization prevents oxidation and self-aggregation, ensuring stable emission signals during analysis. The sensor’s bifunctional monomers create precise recognition sites tailored for CIP molecules, enhancing detection accuracy.

Researchers detailed the synthesis process for CuNWs@PVP, including centrifugation to remove impurities and re-dissolution in deoxidized ethanol to maintain purity. The composite was stored under controlled conditions to prevent degradation. To test its real-world application, pork and fish samples underwent grinding, extraction, and purification using solid-phase extraction (SPE) before ECL analysis.

For detection, the ECL setup electrochemically stimulated the sensors, generating light emissions indicative of CIP presence. Sensitivity assessments across various concentrations and recovery rate calculations were conducted to evaluate the method’s effectiveness.

Results and Implications

The MIECLS sensor demonstrated a linear detection range for CIP between 5.00 × 10-9 mol L-1 and 5.00 × 10-5 mol L-1, with an impressively low detection limit of 2.59 × 10-9 mol L-1. Recovery rates ranged from 84.39 % to 92.48 %, confirming the method’s reliability and accuracy.

These findings suggest a practical, cost-effective alternative to traditional detection techniques, offering an efficient way to monitor antibiotic residues in food. With its enhanced sensitivity and specificity, the sensor presents a valuable tool for routine quality checks, reducing the risks associated with contaminated food products.

This study marks a shift from conventional detection methods toward more advanced, sustainable approaches. The incorporation of bifunctional monomers in MIECLS improves target recognition while maintaining operational simplicity. Additionally, the affordability and accessibility of this method position it as a promising solution for food safety assessments in various settings.

Conclusion

In summary, this research represents a significant step forward in food safety monitoring with the development of a highly sensitive electrochemical sensor based on CuNWs@PVP. By offering a cost-effective and efficient means to detect ciprofloxacin residues, this technique supports proactive food safety measures, helping to protect consumer health. As antibiotic contamination remains a pressing issue, the adoption of innovative detection methods like this one will be essential for ensuring a safer food supply chain.

Journal Reference

Wu J., Qin Y., et al. (2025). Self-Enhanced Near-Infrared Copper Nanoscale Electrochemiluminescence Probe for the Sensitive Detection of Ciprofloxacin in Foods. Foods 14(3):538. DOI: 10.3390/foods14030538, https://www.mdpi.com/2304-8158/14/3/538

Dr. Noopur Jain

Written by

Dr. Noopur Jain

Dr. Noopur Jain is an accomplished Scientific Writer based in the city of New Delhi, India. With a Ph.D. in Materials Science, she brings a depth of knowledge and experience in electron microscopy, catalysis, and soft materials. Her scientific publishing record is a testament to her dedication and expertise in the field. Additionally, she has hands-on experience in the field of chemical formulations, microscopy technique development and statistical analysis.    

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Jain, Noopur. (2025, February 21). New Electrochemical Sensor Enhances Detection of Antibiotic Residues in Food. AZoSensors. Retrieved on February 21, 2025 from https://www.azosensors.com/news.aspx?newsID=16248.

  • MLA

    Jain, Noopur. "New Electrochemical Sensor Enhances Detection of Antibiotic Residues in Food". AZoSensors. 21 February 2025. <https://www.azosensors.com/news.aspx?newsID=16248>.

  • Chicago

    Jain, Noopur. "New Electrochemical Sensor Enhances Detection of Antibiotic Residues in Food". AZoSensors. https://www.azosensors.com/news.aspx?newsID=16248. (accessed February 21, 2025).

  • Harvard

    Jain, Noopur. 2025. New Electrochemical Sensor Enhances Detection of Antibiotic Residues in Food. AZoSensors, viewed 21 February 2025, https://www.azosensors.com/news.aspx?newsID=16248.

Tell Us What You Think

Do you have a review, update or anything you would like to add to this news story?

Leave your feedback
Your comment type
Submit

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.