Artificial networks for spectral resolution of antibiotic residues in bovine milk; Solidification of floating organic droplet in dispersive liquid-liquid microextraction for sample treatment
Date
10/02/2021
Authors
Journal Title
Journal ISSN
Volume Title
Type
Article
Publisher
Elsevier
Series Info
Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy;120449
Scientific Journal Rankings
Abstract
The intensive use of antibiotics in livestock practice has a negative impact on human health and increases
the antibiotic resistance. In this study feasible data interpretation algorithm along with efficient extraction
protocol were combined for selective analysis of three antibiotics in milk samples. Trimethoprim,
sulphamethoxazole and oxytetracycline are widely used antibiotics in veterinary pharmaceuticals. The
studied antibiotics were efficiently extracted from milk samples with solidification of floating organic
droplet in dispersive liquid-liquid microextraction. This extraction protocol was optimized not only to
maximize extraction recoveries but also to approach the lower residue limits specified by European Union.
Artificial neural networks succeeded in resolving spectral overlap between the studied drugs. The network
architecture was optimized and validated for accurate and precise analysis. The proposed method outweighs
the reported chromatographic methods for being simple and inexpensive and compared favorable to official
methods.
Description
Keywords
Antibiotic residue, milk analysis, Artificial neural networks, Solidification of floating organic droplet, dispersive liquid-liquid microextraction