Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry Combined with Chemometrics for Protein Profiling and Classification of Boiled and Extruded Quinoa from Conventional and Organic Crops

dc.contributor.authorGalindo Luján, Rocío del Pilar
dc.contributor.authorPont Villanueva, Laura
dc.contributor.authorQuispe Jacobo, Fredy Enrique
dc.contributor.authorSanz Nebot, María Victoria
dc.contributor.authorBenavente Moreno, Fernando J. (Julián)
dc.date.accessioned2025-05-19T10:20:44Z
dc.date.available2025-05-19T10:20:44Z
dc.date.issued2024-06-17
dc.date.updated2025-05-19T10:20:45Z
dc.description.abstractQuinoa is an Andean crop that stands out as a high-quality protein-rich and gluten-free food. However, its increasing popularity exposes quinoa products to the potential risk of adulteration with cheaper cereals. Consequently, there is a need for novel methodologies to accurately characterize the composition of quinoa, which is influenced not only by the variety type but also by the farming and processing conditions. In this study, we present a rapid and straightforward method based on matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) to generate global fingerprints of quinoa proteins from white quinoa varieties, which were cultivated under conventional and organic farming and processed through boiling and extrusion. The mass spectra of the different protein extracts were processed using the MALDIquant software (version 1.19.3), detecting 49 proteins (with 31 tentatively identified). Intensity values from these proteins were then considered protein fingerprints for multivariate data analysis. Our results revealed reliable partial least squares-discriminant analysis (PLS-DA) classification models for distinguishing between farming and processing conditions, and the detected proteins that were critical for differentiation. They confirm the effectiveness of tracing the agricultural origins and technological treatments of quinoa grains through protein fingerprinting by MALDI-TOF-MS and chemometrics. This untargeted approach offers promising applications in food control and the food-processing industry.
dc.format.extent24 p.
dc.format.mimetypeapplication/pdf
dc.identifier.idgrec749681
dc.identifier.issn2304-8158
dc.identifier.pmid38928847
dc.identifier.urihttps://hdl.handle.net/2445/221104
dc.language.isoeng
dc.publisherMDPI
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.3390/foods13121906
dc.relation.ispartofFoods, 2024, vol. 13, num.12
dc.relation.urihttps://doi.org/10.3390/foods13121906
dc.rightscc-by (c) Galindo-Luján, R. et al., 2024
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceArticles publicats en revistes (Enginyeria Química i Química Analítica)
dc.subject.classificationAgricultura sostenible
dc.subject.classificationQuinoa
dc.subject.classificationTecnologia dels aliments
dc.subject.otherSustainable agriculture
dc.subject.otherQuinoa
dc.subject.otherFood technology
dc.titleMatrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry Combined with Chemometrics for Protein Profiling and Classification of Boiled and Extruded Quinoa from Conventional and Organic Crops
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion

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