期刊
FOOD RESEARCH INTERNATIONAL
卷 164, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.foodres.2022.112160
关键词
Quinoa; Amaranth; Authentication and classification; Nutritional signatures; Univariate and multivariate analysis
Univariate and multivariate analyses were performed to classify and authenticate seeds from different varieties of quinoa and amaranth. Univariate analysis showed differences between species for certain components. PCA analysis separated the samples into two groups, with quinoa seeds having higher contents of certain acids, proteins, sugars, and other components. CDA models achieved 100% probability when classifying the samples as either quinoa or amaranth, indicating good sensitivity.
Univariate (Analysis of Variance_ANOVA) and multivariate (Principal Component Analysis (PCA) and Canonical Discriminant Analysis (CDA)) analyses were performed in order to classi f y and authenticate the seeds from different varieties of quinoa (Chenopodium quinoa Will.), and amaranth (Amarant h u s cruentus L.). The univariate analysis showed differences between species for sucrose, K, Ca, unsaturated fatty acids, and the 0)6/0)3 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 0)6/0)3 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.
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