Quinoa is an Andean grain that is attracting attention worldwide as a high-quality protein-rich food. Nowadays, quinoa foodstuffs are susceptible to adulteration with cheaper cereals. Therefore, there is a need to develop novel methodologies for protein characterization of quinoa. Here, we first developed a matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) method to obtain characteristic mass spectra of protein extracts from 4 different commercial quinoa grains, which group different varieties marketed as black, red, white (from Peru) and royal (white from Bolivia). Then, data preprocessing and peak detection with MALDIquant allowed detecting 47 proteins (being 30 tentatively identified), the intensities of which were considered as fingerprints for multivariate data analysis. Finally, classification by partial least squares-discriminant analysis (PLS-DA) was excellent, and 34 out of the 47 proteins were critical for differentiation, confirming the potential of the methodology to obtain a reliable classification of quinoa grains based on protein fingerprinting.
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| http://dx.doi.org/10.1016/j.foodchem.2022.133895 | DOI Listing |
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