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Identification and Quantification of Ciprofloxacin, Enrofloxacin and Difloxacin Residues in Milk Using Excitation-Emission Fluorescence and Second-Order Standard Addition Methods Publisher



Vali Zade S1 ; Neymeyr K2, 3 ; Sawall M2 ; Khoshayand MR4 ; Abdollahi H5
Authors
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Authors Affiliations
  1. 1. Halal Research Center of IRI, Food and Drug Administration, Ministry of Health and Medical Education, Tehran, Iran
  2. 2. University of Rostock, Institute of Mathematics, Ulmenstraße 69, Rostock, 18057, Germany
  3. 3. Leibniz-Institute for Catalysis, Albert-Einstein-Straße 29a, Rostock, 18059, Germany
  4. 4. Department of Drug and Food Control, Faculty of Pharmacy, Tehran University of Medical Sciences, Iran
  5. 5. Faculty of Chemistry, Institute for Advanced Studies in Basic Sciences, Zanjan, 45195-1159, Iran

Source: Chemometrics and Intelligent Laboratory Systems Published:2023


Abstract

In the presence of non-modeled components and analyte-matrix interaction in real samples, a combination of second-order multivariate calibration and standard addition is desired to achieve accurate results via second-order advantage. Enrofloxacin (ENR), Difloxacin (DIF), and Ciprofloxacin (CIP) are Fluoroquinolones widely considered antibiotic residues in milk. Excitation-emission fluorescence spectra of these antibiotics at pH = 9.1 provide second-order data for identifying and quantifying them in a mixture using second-order calibration modeling. Rank annihilation factor analysis (RAFA) and multivariate curve resolution-alternating least squares (MCR-ALS) with trilinearity constraints are applied to determine the CIP, ENR, and DIF residues in synthetic mixtures and milk using second-order excitation-emission fluorescence spectroscopy. In both methods, the trilinearity constraint guarantees a unique true solution to the spectral profiles of analytes. The combination of second-order standard addition and higher-order calibration modeling with RAFA and MCR-ALS supports the second-order advantage in milk analysis. © 2023