Differentiating, evaluating, and classifying three quinoa ecotypes by washing, cooking and germination treatments, using 1H NMR-based metabolomic approach.

Abstract

We processed three quinoa ecotypes as they are commonly consumed in a daily diet. For the treatments, quinoa seeds were washed, cooked, and/or germinated. Following treated, we used 1H NMR-based metabolomic profiling to explore differences between the ecotypes. Then, for a non-targeted and targeted food fingerprint analysis of samples, we performed multivariable data analyses, including principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA), and hierarchical cluster analysis. From our study, we were able to discriminate each quinoa ecotype regardless of treatment based on its metabolomic profiling. Additionally, we were able to identify 30 metabolites that were useful to determine the effect of each treatment on nutritional composition. Germination increased the content of most metabolites irrespective of ecotype. In general, ecotype CQE_03 was different from ecotypes CQE_01 and CQE_02. Our phytochemical analysis revealed the effects of washing, cooking, and/or germination, particularly on saponins content.