کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8879990 | 1624791 | 2018 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Application of HPLC fingerprint based on acid amide components in Chinese prickly ash (Zanthoxylum)
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
علوم زراعت و اصلاح نباتات
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چکیده انگلیسی
In order to establish a high performance liquid chromatography (HPLC) fingerprint of Chinese prickly ash (Zanthoxylum) based on acid amide components, 38 specimen were collected from Western China. Similarity analysis, hierarchical clustering analysis (HCA) and principal component analysis (PCA) were carried out to analyze the obtained fingerprints. Furthermore, uncertainty and reliability values of the established HPLC fingerprints were evaluated. Similarity values ranged between 0.587 and 0.999 for specimen of Zanthoxylum bungeanum Maxim. and between 0.991 and 0.999 for specimen of Zanthoxylum armatum DC. 17 samples from different habitats were classified by HCA into three groups, i.e. Group I (8 samples), Group II (6 samples) and Group III (3 samples) and were divided into three clusters by PCA. The compound of peak 6 was identified as hydroxyl-β-sanshool. The characteristic compounds of peaks 5, 7, 8, 10, 12 and 13 were tentatively identified by LC-MS as other acid amide compounds. As for credibility analysis, the results showed that the values of macroscopic qualitative reliability and macroscopic quantitative reliability of the reference chromatogram fingerprint were more than 0.9772. Statistical analysis indicated that the HPLC fingerprint technology may be applied for quality assessment and classification of Zanthoxylum.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Industrial Crops and Products - Volume 119, 1 September 2018, Pages 267-276
Journal: Industrial Crops and Products - Volume 119, 1 September 2018, Pages 267-276
نویسندگان
Jingxuan Ke, Yuan Qu, Shanshan Li, Guanghui Shen, Anjun Chen, Qingying Luo, Xingyan Liu, Hejun Wu, Meiliang Li, Biao Pu, Meng Ye, Zhiqing Zhang,