豆科选定分类群的多变量判别

IF 0.7 Q4 BIOLOGY
M. Abdulrahman
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引用次数: 0

摘要

摘要Abdulrahman医学博士,2022。Fabaceae科选定分类群的多元判别。Nusantara Bioscience 15:227-232。尼日利亚是全球热带植被和药用植物最有趣、最多样化的国家之一。Fabaceae科的分类学并不完全清楚,将物种组织成可管理的类群,这有助于分类、保护或生药学研究。本研究的目的是对金莲的叶片进行鉴别。,微孢子虫Perr,Tamarindus indica L,Acacia nilotica(L.)Willd。ex Delile、Abrus pretorius L.、Senna occidentalis(L.)Link、Erythrina senegalensis DC。和Pterocarpus erinaceus Poir。基于矿物元素含量结合多元分析。采集了每种野生生长物种的三个样本。使用SIMCA-P(V.14.1,Umetrics Sweden)进行无监督多变量分析。根据其矿物元素含量形成了五个模型组。物种在PC1上得到了充分的区分,占变异的39.3%。这项研究的证据表明,矿物元素分析和化学计量学的结合产生了一种强大的分类方法。通过生物学研究和化学计学相结合对植物进行分类鉴定是防止掺假或食用含有过量或有害成分的植物的一种很好的方法。然而,仍然需要混合使用分子和发育数据集来明确检查它们之间的联系。
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Multivariate discrimination of selected taxa of the Fabaceae family
Abstract. Abdulrahman MD. 2022. Multivariate discrimination of selected taxa of the Fabaceae family. Nusantara Bioscience 15: 227-232. Nigeria is among the most interesting and diversified countries globally regarding tropical vegetation and medicinal plants. The taxonomy of the Fabaceae family is not entirely clear, to organize species into manageable groups that are helpful for taxonomical, conservational, or pharmacognostic study. This study aimed to discriminate the leaves of Dialium guineense Willd., Detarium microcarpum Guill. & Perr, Tamarindus indica L, Acacia nilotica (L.) Willd. ex Delile, Abrus precatorius L., Senna occidentalis (L.) Link, Erythrina senegalensis DC. and Pterocarpus erinaceus Poir. based on the mineral elements contents coupled with multivariate analysis. Three samples of each wild-growing species were collected. Unsupervised multivariate analysis using SIMCA-P (V.14.1, Umetrics Sweden) was employed. Five model groups were formed based on their mineral element contents. The species were fully discriminated along the PC1, accounting for 39.3% of the variation. Evidence from this study showed that a combination of mineral element analysis and chemometrics yielded a powerful classification method. Taxonomic identification of plants through biological research combined with chemometrics is an excellent method for preventing the adulteration or consumption of plants with excessive contents or harmful ingredients. However, a mix of molecular and developmental datasets is still necessary to explicitly examine their connections.
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