Analytical Chemistry
机器学习辅助紫外可见光谱
Machine-learning-assisted ultraviolet-visible spectroscopyA method utilizing machine learning algorithms to analyze ultraviolet-visible (UV-Vis) spectral data for the identification and quantification of multi-component adulterants in Coptis chinensis / 一种利用机器学习算法分析紫外可见光谱数据，用于黄连多组分掺假识别和定量的方法。
- Knowledge type
- 工艺技术
- First proposed or discovered
- Proposer
- Turkey Farm member
- Creator
- 农场主
- Last updated
- 2026-10-23 21:02:07
Sub-knowledge points
Spectroscopy and Scientific Instrumentation / 工艺技术Adulteration identificationMulti-component analysis
Higher-order knowledge points
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Main parameters and performance indicators
Spectral range: Ultraviolet-visible (UV-Vis)Target: Low-level multi-component adulterationSample: Coptis chinensisMethod: Machine learning-assisted analysis
Open problems
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Related literature
ranked by community starsMachine-learning-assisted ultraviolet-visible spectroscopy for low-level multi-component adulteration identification in Coptis chinensisOpen source
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1 recordsRecord title: Machine-learning-assisted ultraviolet-visible spectroscopy.
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