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.author
Galindo Luján, Rocío del Pilar
dc.contributor.author
Pont Villanueva, Laura
dc.contributor.author
Quispe Jacobo, Fredy Enrique
dc.contributor.author
Sanz Nebot, María Victoria
dc.contributor.author
Benavente Moreno, Fernando J. (Julián)
dc.date.issued
2025-05-19T10:20:44Z
dc.date.issued
2025-05-19T10:20:44Z
dc.date.issued
2024-06-17
dc.date.issued
2025-05-19T10:20:45Z
dc.identifier
2304-8158
dc.identifier
https://hdl.handle.net/2445/221104
dc.identifier
749681
dc.identifier
38928847
dc.description.abstract
Quinoa 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
24 p.
dc.format
application/pdf
dc.format
application/pdf
dc.language
eng
dc.publisher
MDPI
dc.relation
Reproducció del document publicat a: https://doi.org/10.3390/foods13121906
dc.relation
Foods, 2024, vol. 13, num.12
dc.relation
https://doi.org/10.3390/foods13121906
dc.rights
cc-by (c) Galindo-Luján, R. et al., 2024
dc.rights
http://creativecommons.org/licenses/by/4.0/
dc.rights
info:eu-repo/semantics/openAccess
dc.source
Articles publicats en revistes (Enginyeria Química i Química Analítica)
dc.subject
Agricultura sostenible
dc.subject
Quinoa
dc.subject
Tecnologia dels aliments
dc.subject
Sustainable agriculture
dc.subject
Quinoa
dc.subject
Food technology
dc.title
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.type
info:eu-repo/semantics/article
dc.type
info:eu-repo/semantics/publishedVersion


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