Comparative analysis of the multi-element and pharmacological composition of Gastrodia elata blume from different geographic origins

IF 4.8 Q1 AGRICULTURE, MULTIDISCIPLINARY
Yujie Shang , Shunqiang Yang , Qinxiang Chang , Kaize Shen , Shaoning Chen , Zongsuo Liang
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引用次数: 0

Abstract

Gastrodia elata Blume tuber is widely recognized as both a food and medicine substance valued for its nutritional and therapeutic properties. However, environmental factors significantly influence its quality, medicinal efficacy, and overall value, making it crucial to comprehensively understand the quality of G. elata from different geographical origins. This study aims to discriminate G. elata specimens originating from three distinct geographical regions in China through comparative analysis of multi-element composition and pharmacological active ingredients. Using high-performance liquid chromatography (HPLC) and Inductively coupled plasma-Mass Spectrometry (ICP-MS), we quantified 17 elements and 6 active ingredients across the samples. Multivariate statistical methods, including cluster heatmap, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA), were employed to assess compositional differences and identify potential biomarkers. Our results showed significant variations in both the chemical and mineral composition of the samples. Multivariate statistics indicated that HBA, PE, PB, and Fe, K, Ca, Mn, P, Na, Cu, Mg, and B were the potential markers for discrimination of G. elata from Shaanxi, Yunnan, and Guizhou. These findings demonstrate the potential of the developed analytical strategy for the identification and discrimination of G. elata from different regions, which integrated pharmacological composition with multi-element as the potential markers.
不同产地天麻多元素及药理成分比较分析
天麻因其营养和治疗特性而被广泛认为是一种食品和药物。然而,环境因素对其品质、疗效和综合价值的影响显著,因此全面了解不同产地elata的品质至关重要。本研究旨在通过多元素组成和药理活性成分的比较分析,对中国三个不同地理区域的白桦标本进行鉴别。采用高效液相色谱(HPLC)和电感耦合等离子体质谱(ICP-MS)对样品中的17种元素和6种有效成分进行了定量分析。采用多变量统计方法,包括聚类热图、主成分分析(PCA)和正交偏最小二乘判别分析(OPLS-DA)来评估成分差异并识别潜在的生物标志物。我们的结果显示,样品的化学和矿物组成都有显著的变化。多因素统计结果表明,HBA、PE、PB和Fe、K、Ca、Mn、P、Na、Cu、Mg、B是陕西、云南、贵州三地叶黄的潜在鉴别指标。这些结果表明,建立以多元素为潜在标记物的综合药理成分分析策略对不同地区的龙葵进行鉴别和鉴定是有潜力的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.40
自引率
2.60%
发文量
193
审稿时长
69 days
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