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安吉利卡·辛尼斯斯的地理起源使用功能性化合物和基于机器学习的聚变方法的多元元素

Ping Yu¹, Xinwei Yan², Jiashun Hong³

¹State Key Laboratory for Quality Ensurance and Sustainable Use of Dao-di Herbs, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, PR China; Key Laboratory of Biology and Cultivation of Herb Medicine, Ministry of Agriculture and Rural Affairs, Beijing 100700, PR China.

|January 9, 2025

概括

验证Angelica sinensis (AS) 的地理来源对于防止食品欺诈至关重要. 一个K-近邻模型在使用关键化合物和元素数据对AS起源进行分类时实现了100%的准确性.

科学领域:

食品科学食品科学食品科学
农业化学农业化学
药用植物的研究研究.

背景情况:

天使 (AS),一种有价值的药用食品,面临着地理来源欺诈的挑战,影响其安全性和真实性.
建立强大的可追溯性方法对于验证AS的质量和来源至关重要.
地理原产地对药用植物的化学成分和疗效有很大影响.

研究的目的:

开发和验证一种可靠的方法,以验证安吉利卡·西内斯 (AS) 的地理来源.
识别关键的化学和元素标记,表明AS的区域特征.
调查环境因素对AS组成和起源的影响.

主要方法:

从8个不同来源的AS样本中分析了16种功能性化合物和40种多元元素配置文件.
应用三个分类算法,包括K-最近邻居 (KNN).
使用VIP功能和用于模型优化的第二级数据融合进行变量选择.

主要成果:

该K-最近邻居 (KNN) 模型,利用由VIP特征和二级融合识别的22个关键变量,在训练和测试集中实现了100%的预测准确性.
根据其地理来源成功对AS样品进行分类.
确定影响AS特征的5个关键环境因素 (经度,度,阴离交换能力,累积温度和干湿度指数).

结论:

开发的KNN模型为Angelica sinensis (AS) 的地理来源认证提供了一个高度准确和有效的工具.
该研究强调了综合化学和元素分析对于确保食品可追溯性和防止欺诈的重要性.
环境因素在塑造不同地区的AS独特配置文件方面发挥着重要作用.

关键词:

天使 (Oliv.) 的一个. 迪尔斯·迪尔斯是什么意思环境因素环境因素功能性化合物是一种功能性化合物.地理来源地理来源多元元素的多元元素.

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