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 |
|