首页|Edible seeds clustering based on phenolics and antioxidant activity using multivariate analysis

Edible seeds clustering based on phenolics and antioxidant activity using multivariate analysis

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Edible seeds, especially those known by the population as nuts, have their consumption associated with func-tional appeal. The present study aimed to compare and group nine different seeds, traditional and regional, according to their similarities, in terms of moisture, total phenolic compounds (TPC) and antioxidant activity, through multivariate analyses. All results were submitted to Principal Component Analysis (PCA), Hierarchical Clusters (HCA) and Kohonen's self-organizing maps (ANN/KSOM). The seeds differed in terms of moisture content, TPC and antioxidant activity. The walnut butterfly stood out with the highest levels of TPC and anti-oxidant activity. In the multivariate analyses application, three groups were formed: i) hazel, baru, Brazil, macadamia, almond and cashew; ii) pequi and marolo; iii) walnut butterfly. It is concluded that the seeds can be separated into three groups, with ANN/KSOMs being the most self-explanatory analysis and that regional seeds are nutritionally similar to those traditionally consumed.

Bioactive compoundsNutsPrincipal component analysisHierarchical clusters analysisArtificial neural network

Araujo de Barros, Hanna Elisia、Silveira Alexandre, Ana Claudia、Campolina, Gabriela Aguiar、Alvarenga, Gabriela Fontes、dos Santos Ferraz e Silva, Lara Maria、Lima Natarelli, Caio Vinicius、Nunes Carvalho, Elisangela Elena、de Barros Vilas Boas, Eduardo Valerio

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Univ Fed Lavras, Food Sci Dept, BR-37200900 Lavras, MG, Brazil

Univ Fed Sao Carlos, Grad Program Mat Sci & Engn, BR-13565905 Sao Carlos, SP, Brazil

2021

LWT-Food Science & Technology

LWT-Food Science & Technology

ISSN:0023-6438
年,卷(期):2021.152
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