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Application-Specific Measurement Uncertainty Software for Measuring Enrofloxacin Residue in Aquatic Products Using
Bo Rong1,2,3,4,5, Haitao Zhang6, Wenjing He2
1School of Marine Technology and Environment, Dalian Ocean University, Dalian 116023, China.
Biology
|January 28, 2026
Summary
A new mobile app, AquaUncertainty Pal, improves the reliability of Quick Quantitative immunoassays for detecting enrofloxacin and ciprofloxacin residues in aquaculture by integrating real-time measurement uncertainty calculations.
Area of Science:
- Food Science
- Analytical Chemistry
- Environmental Science
Background:
- Quick Quantitative (QQ) immunoassays are widely used for enrofloxacin (ENR) and ciprofloxacin (CIP) residue analysis in aquaculture.
- Limited quantitative reliability of QQ methods stems from the infrequent consideration of measurement uncertainty (MU) in field testing.
Purpose of the Study:
- To develop a mobile application, AquaUncertainty Pal, for real-time MU computation within the QQ workflow.
- To enhance the metrological reliability and accuracy of aquaculture residue analysis.
Main Methods:
- Development of a mobile application integrating real-time MU computation into QQ immunoassays.
- Software automatically assesses uncertainty sources in sampling and pipetting, visualizes uncertainty budgets, and guides users.
- Validation against ISO/IEC 17025-accredited LC-MS/MS and a user study with 20 technicians.
Main Results:
- Integrated software improved pipetting precision (RSD at 100 μL from 4.1% to 1.79%).
- Reduced inter-operator variability (CV) by 52%.
- Increased conformity assessment accuracy near the maximum residue limit (MRL) from 25% to 70%.
Conclusions:
- Real-time MU visualization effectively guides technicians towards consistent pipetting and interpretation.
- Integrating MU into QQ workflows is feasible and effective for improving residue analysis reliability.
- The digital framework supports uncertainty-informed residue monitoring in aquaculture.
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