National Electronics and Computer Technology Center, 112 Thailand Science Park, Pathum Thani 12120, Thailand.
College of Materials Innovation and Technology, King Mongkut's Institute of Technology Ladkrabang (KMITL), Bangkok 10520, Thailand.
Spectrochim Acta A Mol Biomol Spectrosc. 2023 Jul 5;295:122584. doi: 10.1016/j.saa.2023.122584. Epub 2023 Mar 7.
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 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.
表面增强拉曼光谱（SERS）已被广泛研究并被认为是一种用于痕量化学分析的强大无标记技术。然而，其同时识别几种分子物种的缺点极大地限制了其实际应用。在这项工作中，我们报告了 SERS 和独立成分分析（ICA）的组合，用于检测水产养殖中常用的几种痕量抗生素，包括孔雀石绿、呋喃唑酮、呋喃他酮盐酸盐、呋喃妥因和呋喃唑酮。分析结果表明，ICA 方法在分解测量的 SERS 光谱方面非常有效。当适当优化成分数量和每个独立成分加载的符号时，可以精确识别目标抗生素。使用 SERS 基底，优化的 ICA 可以在 10M 的浓度下识别混合物中的痕量分子，达到与参考分子光谱的相关值为 71-98%。此外，从实际样品的测量结果也可以识别出来，这为该方法在实际水生环境中监测抗生素提供了重要依据。
