Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/172184
Title: Classification of quinoa varieties based on protein fingerprinting by capillary electrophoresis with ultraviolet absorption diode array detection and advanced chemometrics
Author: Galindo-Luján, Rocío
Pont Villanueva, Laura
Sanz Nebot, María Victoria
Benavente Moreno, Fernando J. (Julián)
Keywords: Proteïnes
Cereals (Aliment)
Química dels aliments
Proteins
Grain (feed)
Food composition
Issue Date: 28-Sep-2020
Publisher: Elsevier B.V.
Abstract: Quinoa (Chenopodium quinoa Willd.) is an andean grain with exceptional nutritional properties that has been progressively introduced in western countries as a protein-rich super food with a broad amino acid spectrum. Quinoa is consumed as whole grain, but it is also milled to produce high-value flour, which is susceptible to adulteration. Therefore, there is a growing interest in developing novel analytical methods to get further information about quinoa at the chemical level. In this study, we developed a rapid and simple capillary electrophoresis-ultraviolet absorption diode array detection (CE-UV-DAD) method to obtain characteristic multiwavelength electrophoretic profiles of soluble protein extracts from different quinoa grain varieties. Then, advanced chemometric methods (i.e. multivariate curve resolution alternating least squares, MCR-ALS, followed by principal component analysis, PCA, and partial least squares discriminant analysis, PLS-DA) were applied to deconvolute the components present in the electropherograms and classify the quinoa varieties according to their differential protein composition.
Note: Versió postprint del document publicat a: https://doi.org/10.1016/j.foodchem.2020.128207
It is part of: Food Chemistry, 2020, vol. 341, p. 128207
URI: http://hdl.handle.net/2445/172184
Related resource: https://doi.org/10.1016/j.foodchem.2020.128207
ISSN: 0308-8146
Appears in Collections:Articles publicats en revistes (Enginyeria Química i Química Analítica)

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