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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/172184
Classification of quinoa varieties based on protein fingerprinting by capillary electrophoresis with ultraviolet absorption diode array detection and advanced chemometrics
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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.
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GALINDO-LUJÁN, Rocío, et al. Classification of quinoa varieties based on protein fingerprinting by capillary electrophoresis with ultraviolet absorption diode array detection and advanced chemometrics. Food Chemistry. 2020. Vol. 341, num. 128207. ISSN 0308-8146. [consulted: 10 of June of 2026]. Available at: https://hdl.handle.net/2445/172184