| 裴正阳，鲁同所.天麻的红外光谱分析及特征识别[J].中医药信息,2025,42(3):1-5 |
| 天麻的红外光谱分析及特征识别 |
| Infrared Spectroscopy Analysis and Feature Identification of Gastrodia Elata |
| 投稿时间：2024-08-26 录用日期：2024-10-09 |
| DOI：10.19656/j.cnki.1002-2406.20250301 |
| 中文关键词: 天麻 红外光谱 系统聚类分析 |
| 英文关键词: Gastrodia elata Infrared spectroscopy Systematic cluster analysis |
| 基金项目: |
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| 摘要点击次数: 135 |
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| 中文摘要: |
| 目的：基于红外光谱分析技术，利用其无损、高通量及能够反映分子层面信息的特点，实现对天麻药材质量的快速评估。方法：选取8种不同的天麻药材样品，经过清洗、干燥、粉碎过筛处理后，与KBr混合制成压片，采用中红外区透过率模式采集红外光谱数据；利用GS平滑、一阶导数、二阶导数、归一化等多种预处理方法来消除背景、噪声等干扰因素，提高光谱分析的精度和准确性。结果：所有天麻样本在3 432、2 930、1 640、1 420、1 020、568 cm-1处展现出6个共有的特征吸收峰，反映了样本间化学组成的相似性；特别是1 640、1 420 cm-1处的吸收峰，是天麻样品中芳香环成分的特征标志；在一阶导图、二阶导图处理后的光谱图谱上，发现云南天麻与西藏天麻在2 800～3 000 cm-1和1 000～1 100 cm-1波数范围内有显著差异；根据光谱特征利用聚类分析可以鉴别种植天麻和野生天麻。结论：红外光谱技术结合聚类分析能够区分不同生长环境、不同栽培方式的天麻样品；通过特征吸收峰的比对，可观察到天麻中关键化学成分的分布规律。红外光谱分析可作为天麻药材的质量控制、真实性和产地追溯的有效方法。 |
| 英文摘要: |
| Objective： To achieve rapid quality evaluation of Gastrodia elata using infrared spectroscopy， which is non－destructive， high－throughput， and capable of reflecting molecular－level information. Methods： Eight different samples of Gastrodia elata were selected， cleaned， dried， pulverized， and sieved before being mixed with KBr to form tablets. Infrared spectra were collected in the mid－infrared transmission mode. Various preprocessing methods such as GS smoothing， first derivative， second derivative， and normalization were employed to eliminate background noise and enhance analytical precision and accuracy. Results： All samples exhibited six common characteristic absorption peaks at 3 432， 2 930， 1 640， 1 420， 1 020， and 568 cm-1， indicating chemical composition similarity among the samples. The peaks at 1 640 and 1 420 cm-1 were identified as markers of aromatic ring components in Gastrodia elata. Differences between Yunnan and Tibet Gastrodia elata samples were observed in the 2 800－3 000 cm-1 and 1 000－1 100 cm-1 ranges after first－and second－derivative processing. Cluster analysis based on spectral characteristics successfully distinguished cultivated from wild Gastrodia elata. Conclusion： Infrared spectroscopy combined with cluster analysis can differentiate Gastrodia elata samples based on growth environment and cultivation methods. By comparing characteristic absorption peaks， key chemical component distributions in Gastrodia elata can be observed. Infrared spectroscopy is an effective tool for quality control， authenticity verification， and traceability of Gastrodia elata. |
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