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使用太赫兹光谱学和深度学习快速识别Rhizoma Coptidis的起源

Xiaofeng Zhang¹, Hualin Chen¹, Xianyou Qu²

¹School of Electronics and Electrical Engineering, Chongqing university of Science and Technology, Chongqing, China.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy

|December 9, 2025

概括

这项研究使用太赫兹光谱学和一种新的ICOA-GRU-MSA模型来确定Rhizoma Coptidis (RC) 的地理来源. 这种先进的模型准确地区分微妙的光谱差异,使得传统中医药可靠的来源识别.

科学领域:

分析化学分析化学
频谱学是一种光谱学.
计算化学的计算化学

背景情况:

根据地理来源,Rhizoma Coptidis (RC) 的质量和有效性有很大差异.
准确识别RC来源对于确保中国传统医学 (TCM) 的质量控制和治疗一致性至关重要.
传统的原产地识别方法可能耗时,可能需要复杂的样本准备.

研究的目的:

开发一种快速,非破坏性的方法来确定Rhizoma Coptidis (RC) 的地理来源.
为了评估太赫兹时域光谱学 (THz-TDS) 与RC来源识别的新型分类模型相结合的有效性.
建立一种新的方法来确定TCM的原产地.

主要方法:

太赫兹时域光谱法 (THz-TDS) 用于对来自四个不同地理来源的RC样本进行非破坏性分析.
提出了一个新的分类模型,ICOA-GRU-MSA,将ICOA集成为GRU超参数优化和MSA用于增强特征识别.
将ICOA-GRU-MSA模型的性能与基于THz光谱的其他RC来源识别模型进行了比较.

主要成果:

RC样本的太赫兹光谱表现出微妙的差异,这给直接来源确定带来了挑战.
与其他模型相比,拟议的ICOA-GRU-MSA模型显示出优越的学习能力和分类性能.
该模型通过分析它们的太赫兹光谱,成功地确定了RC样本的起源.

结论:

太赫兹时域光谱学为分析传统中医提供了一种有前途的非破坏性技术.
该ICOA-GRU-MSA模型提供了一种有效和准确的方法来确定Rhizoma Coptidis的地理来源.
本研究提出了一种新的计算方法,用于TCM的原产地识别,增强质量控制和研究.

关键词:

这就是ICOA-GRU-MSA模型.原产地标识来源标识根茎瘤复合性疾病根茎瘤太赫兹光谱学是一次特拉赫兹光谱学.

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