Application-Specific Measurement Uncertainty Software for Measuring Enrofloxacin Residue in Aquatic Products Using the Quick Quantitative (QQ) Method

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Authors: Bo Rong, Haitao Zhang, Wenjing He, Peilong Song, Yuanyuan Xu, Emmanuel Bob Samuel Simbo, Haizhou Jiang, Liping Qiu, Lei Zhu, Longxiang Fang, Suxian Qi, Tingting Yang
+3 more Zhongquan Jiang, Shunlong Meng, Chao Song
Cited by: 0
References: 36

Abstract

Quick Quantitative (QQ) immunoassays have been increasingly applied for the measurement of enrofloxacin (ENR) and ciprofloxacin (CIP) residues in aquaculture due to their speed and convenience. However, their quantitative reliability remains limited because measurement uncertainty (MU) is rarely considered during field testing. To enhance the metrological reliability of QQ-based residue analysis, we developed AquaUncertainty Pal, a mobile application that embeds real-time MU computation into the QQ workflow. The software automatically evaluates uncertainty sources during sampling and pipetting, visualizes the uncertainty budget, and guides users through optimized operations. The framework was validated against ISO/IEC 17025-accredited LC-MS/MS and assessed through a user study involving 20 frontline technicians. With the integrated software, pipetting precision (RSD) at 100 μL improved from 4.1% to 1.79%, the inter-operator variability (CV) decreased by 52%, and conformity assessment accuracy for samples near the maximum residue limit (MRL) increased from 25% to 70%. This suggests that real-time MU visualization effectively guided technicians toward consistent pipetting and interpretation behavior. These results demonstrate that integrating MU into the QQ workflow is both feasible and effective, substantially improving reliability and providing a replicable digital framework for uncertainty-informed residue monitoring in aquaculture.

Fields of Study & Subjects

Pesticide Residue Analysis and Safety Antibiotics Pharmacokinetics and Efficacy Pharmaceutical and Antibiotic Environmental Impacts

Publication details

Journal / source
Biology
Volume
15
Issue
2
Pages
119–119
Publication date
7 January 2026
Language
EN