研究不同预处理方法对不同激发波长记录的拉曼光谱的影响
Sara Mostafapour1, Thomas Dörfer2, Ralf Heinke2
1Leibniz Institute of Photonic Technology, Member of Leibniz Health Technologies, Member of the Leibniz Centre for Photonics in Infection Research (LPI), Albert‑Einstein‑Straße 9, 07745 Jena, Germany; Institute of Physical Chemistry (IPC) and Abbe Center of Photonics (ACP), Friedrich Schiller University Jena, Member of the Leibniz Centre for Photonics in Infection Research (LPI), Helmholtzweg 4, 07743 Jena, Germany.
拉曼光谱数据的预处理对于准确的样本识别至关重要. 优化预处理方法可以提高光谱的一致性,提高分类模型的准确性,尽管最佳策略因数据集而异.
科学领域:
- 分析化学 分析化学
- 频谱学是一种光谱学.
- 化学测量 化学测量 化学测量
背景情况:
- 拉曼光谱为识别样品组件提供独特的指纹信息.
- 由于实验条件的光谱变化挑战了拉曼参考库的可靠性.
- 数据的预处理对于最大限度地减少由不同的实验条件引起的光谱差异至关重要.
研究的目的:
- 量化不同拉曼数据预处理方法对光谱一致性的影响.
- 评估预处理组合在最小化不同激发波长的光谱变异方面的有效性.
- 评估预处理对分类模型性能的影响.
主要方法:
- 应用各种预处理方法组合到六种溶剂的拉曼光谱.
- 通过使用三种激发波长 (532 nm, 633 nm, 830 nm) 的角差指数来评估光谱差异.
- 测试了预处理对光谱分类模型的影响.
主要成果:
- 波数校准证明了光谱差异的最显著减少.
- 欧米茄-4 (ω4) 校正对测试数据集没有显著影响.
- 数据预处理始终提高了分类预测的准确性.
- 预处理步骤的最佳数量因激发波长和数据集特征而异.
结论:
- 选择拉曼数据预处理方法显著影响分析结果.
- 有效的预处理需要仔细考虑数据集的具体情况和分析目标.
- 没有普遍的预处理策略可以保证所有拉曼光谱应用的最佳结果.
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