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Geographical Origin Authentication of Edible Chrysanthemum morifolium Ramat. (Hangbaiju) Using Stable Isotopes

文献类型： 外文期刊

作者： Mei, Hanyi 1 ; Nie, Jing 1 ; Wang, Shu 2 ; Zhang, Yongzhi 1 ; Li, Chunlin 1 ; Shao, Shengzhi 1 ; Shao, Shanshan 2 ; Rogers, Karyne M. 1 ; Yuan, Yuwei 1 ;

作者机构： 1.Inst Agroprod Safety & Nutr, Zhejiang Acad Agr Sci, Key Lab Informat Traceabil Agr Prod, Minist Agr & Rural Affairs China, Hangzhou 310021, Peoples R China

2.Zhejiang Longev Valley Bot Co Ltd, Jinhua 321200, Peoples R China

3.Natl Isotope Ctr, GNS Sci, Lower Hutt 5040, New Zealand

关键词： Chrysanthemum morifolium Ramat; Hangbaiju; stable isotopes; separation; geographical origin identification; traditional medicine

期刊名称：SEPARATIONS （ 影响因子：2.6； 五年影响因子：2.7 ）

ISSN：

年卷期： 2023 年 10 卷 5 期

页码：

收录情况： SCI

摘要： Chrysanthemum morifolium Ramat., known as Hangbaiju (HBJ), is a high-value edible, medicinal product where the flowers are infused in hot water and drunk as tea. Its quality and efficacy are closely related to its geographical origin. Consequently, it is vulnerable to fraudulent substitution by other lower-value Chrysanthemum products. In this study, cultivation (variety and different growth stages) and isotopic fractionation between the flower, stem, and leaf were studied. Samples from four different HBJ varieties were characterized using stable isotopes (d(13)C, d(15)N, d(2)H, d(18)O, %C, and %N) across three producing regions in Zhejiang province, China. The results showed that there were no significant differences in stable isotopic compositions for different HBJ varieties, but there were significant differences for different plant tissues (flower, stem, leaf, etc.). Furthermore, the stable isotopic composition altered dramatically at different growth stages. The d(15)N (r = 0.6809) and d(2)H (r = 0.6102) correlations between stems and leaves (SL) and flowers (F) of HBJ were relatively good, the d(13)C correlation (r = 0.2636) between SL and F was weak, but d(18)O correlation (r = 0.01) had almost no correlation. A supervised multivariate statistical model (partial least squares discriminant analysis, PLS-DA) was used to discriminate three different producing regions with high accuracy (66.7%, 66.7%, and 100%, respectively). Our findings show that stable isotopes combined with multivariate statistical analysis provide an effective method for the geographical identification of HBJ.

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