Metabolomic profile and discrimination of white quinoa seeds from Peru based on UHPLC-HRMS and multivariate analysis

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