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A Hybrid Lab-on-a-Chip Injector System for Autonomous Carbofuran Screening.

Aristeidis S Tsagkaris1, Jana Pulkrabova1, Jana Hajslova1

  • 1Department of Food Analysis and Nutrition, Faculty of Food and Biochemical Technology, University of Chemistry and Technology Prague, Technická 5, 6-Dejvice, 166 28 Prague, Czech Republic.

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Summary
This summary is machine-generated.

A new hybrid paper-lab-on-a-chip platform enables affordable, smartphone-based prescreening for pesticide residues. This technology accurately detects carbofuran, a banned neurotoxic pesticide, in food samples.

Keywords:
3D-printed devicesacetylcholinesterasefood safetylab-on-a-chipmicrofluidicspesticidesscreening method

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Area of Science:

  • Food safety analysis
  • Analytical chemistry
  • Microfluidics

Background:

  • Ensuring food safety requires robust methods to detect contaminants like pesticide residues.
  • Current reference methods for pesticide residue analysis are costly and time-consuming, necessitating advanced prescreening tools.
  • The presence of neurotoxic pesticides, such as carbofuran, poses significant public health risks.

Purpose of the Study:

  • To develop a novel, integrated paper-based microfluidic device for rapid and affordable pesticide residue detection.
  • To enable semiquantitative analysis of carbofuran using a smartphone-based detection system.
  • To validate the platform's efficacy in real-world food sample matrices.

Main Methods:

  • A hybrid paper-lab-on-a-chip platform with on-demand injectors was designed for multi-step protocols.
  • Simultaneous detection of enzymatic colorimetric responses in sample and reference cells was performed.
  • A standard smartphone camera was utilized for semiquantitative analysis of the colorimetric signals.
  • The platform was applied to detect carbofuran in apple extracts, with a focus on dynamic response evaluation.

Main Results:

  • The developed platform achieved semiquantitative detection of carbofuran across a broad concentration range.
  • The system demonstrated high specificity and accuracy, effectively rejecting spurious measurements.
  • The method was successfully applied for the binary detection of carbofuran in apple extracts, confirming its practical utility.

Conclusions:

  • The hybrid paper-lab-on-a-chip platform offers a smart, affordable, and efficient solution for pesticide residue prescreening.
  • Smartphone integration provides a user-friendly and accessible detection method for food safety applications.
  • This technology holds significant potential for improving food safety monitoring and protecting public health.