Label free detection of multiple trace antibiotics with SERS substrates and independent components analysis

表面增强拉曼光谱 呋喃西林 独立成分分析 硝基呋喃 生物系统 呋喃妥因 化学 分析化学(期刊) 拉曼光谱 色谱法 抗生素 计算机科学 拉曼散射 人工智能 生物 光学 物理 传统医学 医学 生物化学 环丙沙星 遗传学
作者
Saksorn Limwichean,Wipawanee Leung,Pemika Sataporncha,Nongluck Houngkamhang,On-Uma Nimittrakoolchai,Bunpot Saekow,Tawee Pogfay,Pacharamon Somboonsaksri,Jia Yi Chia,Raju Botta,Mati Horprathum,Supanit Porntheeraphat,Noppadon Nuntawong
出处
期刊:Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy [Elsevier BV]
卷期号:295: 122584-122584 被引量:16
标识
DOI:10.1016/j.saa.2023.122584
摘要

Surface enhanced Raman spectroscopy (SERS) has been widely studied and recognized as a powerful label-free technique for trace chemical analysis. However, its drawback in simultaneously identifying several molecular species has greatly limited its real-world applications. In this work, we reported a combination between SERS and independent component analysis (ICA) to detect several trace antibiotics which are commonly used in aquacultures, including malachite green, furazolidone, furaltadone hydrochloride, nitrofurantoin, and nitrofurazone. The analysis results indicate that the ICA method is highly effective in decomposing the measured SERS spectra. The target antibiotics could be precisely identified when the number of components and the sign of each independent component loading were properly optimized. With SERS substrates, the optimized ICA can identify trace molecules in a mixture at a concentration of 10-6 M achieving the correlation values to the reference molecular spectra of 71-98%. Furthermore, measurement results obtained from a real-world sample demonstration could also be recognized as an important basis to suggest this method is promising for monitoring antibiotics in a real aquatic environment.
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