Suppr超能文献

区分籽粒苋和藜麦种子的独特营养特性。

Unique nutritional features that distinguish Amaranthus cruentus L. and Chenopodium quinoa Willd seeds.

作者信息

José Rodríguez Gómez María, Maestro-Gaitán Isaac, Calvo Magro Patricia, Cruz Sobrado Verónica, Reguera Blázquez María, Matías Prieto Javier

机构信息

Technological Institute of Food and Agriculture of Extremadura (CICYTEX), Avda. Adolfo Suárez, s/n, 06007 Badajoz, Spain.

Department of Biology, Campus de Cantoblanco, c/Darwin 2, Universidad Autónoma de Madrid, 28049 Madrid, Spain.

出版信息

Food Res Int. 2023 Feb;164:112160. doi: 10.1016/j.foodres.2022.112160. Epub 2022 Dec 5.

Abstract

Univariate (Analysis of Variance_ANOVA) and multivariate (Principal Component Analysis (PCA) and Canonical Discriminant Analysis (CDA)) analyses were performed in order to classify and authenticate the seeds from different varieties of quinoa (Chenopodium quinoa Will.), and amaranth (Amaranthus cruentus L.). The univariate analysis showed differences between species for sucrose, K, Ca, unsaturated fatty acids, and the ω6/ω3 ratio. Nevertheless, to strengthen this classification, a PCA was applied separating the samples in 2 groups; group 1, formed by quinoa seeds, presented higher contents of margaroleic, eicosadienoic, behenic, erucic, linolenic, linoleic, and gadoleic acids, proteins, sucrose, and total sugars. Group 2, formed by amaranth seeds, showed positive values for Mn, Mg, Fe, P, Zn, Ca, fiber, glucose, and ω6/ω3 ratio. Furthermore, the CDA models developed resulted in a probability of event of 100% when classifying the samples in the groups quinoa or amaranth, highlighting the good sensitivity of the models used.

摘要

为了对藜麦(Chenopodium quinoa Will.)和苋菜(Amaranthus cruentus L.)不同品种的种子进行分类和鉴定,进行了单变量(方差分析_ANOVA)和多变量(主成分分析(PCA)和典型判别分析(CDA))分析。单变量分析显示,不同物种在蔗糖、钾、钙、不饱和脂肪酸和ω6/ω3比值方面存在差异。然而,为了强化这种分类,应用主成分分析将样本分为两组;第1组由藜麦种子组成,其含有较高含量的十七碳一烯酸、二十碳二烯酸、山嵛酸、芥酸、亚麻酸、亚油酸和gadoleic酸、蛋白质、蔗糖和总糖。第2组由苋菜种子组成,其锰、镁、铁、磷、锌、钙、纤维、葡萄糖和ω6/ω3比值呈正值。此外,所建立的典型判别分析模型在将样本分类为藜麦或苋菜组时,事件概率为100%,突出了所用模型的良好敏感性。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验