一个基于二酸的光传感器阵列,用于快速识别Lonicerae Japonicae Flos和Lonicerae Flos
Ying Bian1, Chenqing Xiang1, Yi Xu2
1School of Pharmacy, Hubei University of Science and Technology, Xianning 437100, China.
Molecules (Basel, Switzerland)
|September 28, 2024
概括
这项研究引入了一种新的光传感器阵列和机器学习,以准确区分Lonicerae japonicae flos (LJF) 和Lonicerae flos (LF). 这种方法可以确保正确识别这些传统的中国草药,防止药物替代.
科学领域:
- 分析化学 分析化学
- 生物化学 生物化学
- 药理学是指药理学,即药理学是指药理学.
背景情况:
- 龙 (Lonicerae japonicae flos,简称LJF) 和龙 (Lonicerae flos,简称LF) 是中国传统的草药,尽管外表相似,但具有独特的药用特性.
- 精确的区分至关重要,因为它们在临床应用中是不可互换的.
研究的目的:
- 开发一种快速准确的方法来区分LJF和LF.
- 为了利用先进的传感器技术和机器学习来进行草本认证.
主要方法:
- 设计了一个六通道光传感器阵列,使用基于库马林的指示器和二博酸火器.
- 用指标位移试验 (IDA) 来检测酸化合物.
- 优化了8个机器学习算法,其中线性差异分析 (LDA) 显示出最佳性能.
主要成果:
- 传感器阵列成功地根据不同的光回收模式区分了LJF和LF.
- 优化的机器学习模型在测试组中实现了100%的准确性,在交叉验证中达到98.21%的准确性.
- 该方法在区分两种草本物种方面表现出高效.
结论:
- 集成的光传感器阵列和机器学习方法为识别LJF和LF提供了强大的工具.
- 这项技术对含有多的食品和药品的分析和质量控制具有重大潜力.
- 确保准确识别传统中国草药,支持安全有效的药用.
关键词:
单鱼类 (Lonicerae) 的牙线有孤单的日语字母 (Lonicerae japonicae flos) 是一个日本字母.光传感器阵列是一组光传感器阵列.机器学习是机器学习.快速识别快速识别更多相关视频
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