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四种传统埃塞俄比亚画眉草品牌的金属(类)物质特征:地理起源鉴别。

Metal(loid)s Profile of Four Traditional Ethiopian Teff Brands: Geographic Origin Discrimination.

机构信息

Department of Soil and Water Resources Management, Wollo University, Dessie, Ethiopia.

College of Southern Nevada, Las Vegas, NV, USA.

出版信息

Biol Trace Elem Res. 2024 Mar;202(3):1305-1315. doi: 10.1007/s12011-023-03736-7. Epub 2023 Jun 28.

Abstract

Among the most renowned Ethiopian food crops, teff (Eragrostis tef (Zucc.)Trotter) is the most nutritious and gluten-free cereal. Because of the increase in demand for teff, it is necessary to establish geographic origin authentication of traditional teff brands based on multi-element fingerprint. For this purpose, a total of 60 teff samples were analysed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Accuracy of the laboratory procedure was verified by the analysis of rice flour standard reference material (NIST SRM 1568b). In this context, four traditional teff brands (Ada'a, Ginchi, Gojam and Tulu Bolo) were analytically characterized using multi-element fingerprint and further treated statistically using linear discriminant analysis (LDA). Due to obvious extrinsic Fe, Al and V contamination, these elements were excluded from the discriminant model. Five elements (Cu, Mo, Se, Sr, and Zn) significantly contributed to discriminate the geographical origin of white teff. On the other hand, Mn, Mo, Se and Sr were used as discriminant variables for brown teff. LDA revealed 90 and 100% correct classifications for white and brown teff, respectively. Overall, multi-element fingerprint coupled with LDA can be considered a suitable tool for geographic origin discrimination of traditional teff brands.

摘要

在最著名的埃塞俄比亚粮食作物中,埃塞俄比亚画眉草(Eragrostis tef (Zucc.)Trotter)是最有营养和无麸质的谷物。由于对埃塞俄比亚画眉草的需求不断增加,有必要基于多元素指纹建立传统埃塞俄比亚画眉草品牌的地理起源认证。为此,使用电感耦合等离子体质谱法(ICP-MS)分析了总共 60 个埃塞俄比亚画眉草样品。通过对米粉标准参考物质(NIST SRM 1568b)的分析,验证了实验室程序的准确性。在这种情况下,使用多元素指纹分析并进一步使用线性判别分析(LDA)进行统计处理,对四个传统埃塞俄比亚画眉草品牌(Ada'a、Ginchi、Gojam 和 Tulu Bolo)进行了分析。由于明显的外部 Fe、Al 和 V 污染,这些元素被排除在判别模型之外。五个元素(Cu、Mo、Se、Sr 和 Zn)对区分白埃塞俄比亚画眉草的地理起源有显著贡献。另一方面,Mn、Mo、Se 和 Sr 被用作区分棕色埃塞俄比亚画眉草的判别变量。LDA 分别对白色和棕色埃塞俄比亚画眉草的正确分类率为 90%和 100%。总的来说,多元素指纹与 LDA 相结合可以被认为是传统埃塞俄比亚画眉草品牌地理起源鉴别合适的工具。

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