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dc.contributor.author | Cabanillas Amado, Billy Joel | |
dc.contributor.author | Espichán, Fabio | |
dc.contributor.author | Estrada, Rigoberto | |
dc.contributor.author | Neyra Valdez, Lidio Edgar | |
dc.contributor.author | Rojas, Rosario | |
dc.date.accessioned | 2022-03-24T21:47:43Z | |
dc.date.available | 2022-03-24T21:47:43Z | |
dc.date.issued | 2021 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12866/11507 | |
dc.description.abstract | In the present work, an untargeted metabolomic approach based on ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC–HRMS) was performed for the discrimination of 25 accessions of white quinoa from main production zones of Peru. From the fingerprint analysis, a total of eighty-four metabolites were tentatively identified based on their accurate mass measurements and MS/MS data. Among them, forty-six compounds are reported here for the first time in C. quinoa (eight phenolics, one ecdysteroid, and thirty-seven saponins), twenty-four of them would correspond to new structures. Principal component analysis (PCA) and orthogonal partial least square discriminant analysis (OPLS-DA) were used to analyze the metabolomic data. As a result, the samples were distributed into two groups. The compounds contributing to the differences between these groups were identified by S-plot analysis. | en_US |
dc.language.iso | eng | |
dc.publisher | Elsevier | |
dc.relation.ispartofseries | Journal of Cereal Science | |
dc.rights | info:eu-repo/semantics/restrictedAccess | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es | |
dc.subject | Chenopodium quinoa | en_US |
dc.subject | Metabolomic profile | en_US |
dc.subject | UHPLC-MS | en_US |
dc.subject | Principal component analysis | en_US |
dc.title | Metabolomic profile and discrimination of white quinoa seeds from Peru based on UHPLC-HRMS and multivariate analysis | en_US |
dc.type | info:eu-repo/semantics/article | |
dc.identifier.doi | https://doi.org/10.1016/j.jcs.2021.103307 | |
dc.relation.issn | 0733-5210 |
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