Detection of quinoa flour adulteration by means of FT-MIR spectroscopy combined with chemometric methods

Quinoa flour has been receiving an increasing attention as a substitute for wheat flour in bread formulations due to immuno-nutritional features. This growing interest in quinoa has increased the demand and consequently the prices, being a target for possible adulterations with cheaper cereals. Four...

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Detalles Bibliográficos
Autores: Rodríguez, Silvio David, Rolandelli, Guido, Buera, Maria del Pilar
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2019
País:Argentina
Institución:Consejo Nacional de Investigaciones Científicas y Técnicas
Repositorio:CONICET Digital (CONICET)
Idioma:inglés
OAI Identifier:oai:ri.conicet.gov.ar:11336/113187
Acceso en línea:http://hdl.handle.net/11336/113187
Access Level:acceso abierto
Palabra clave:CHEMOMETRIC METHODS
FT-IR
PLS-DA
QUINOA FLOUR ADULTERATION
SIMCA
https://purl.org/becyt/ford/2.11
https://purl.org/becyt/ford/2
Descripción
Sumario:Quinoa flour has been receiving an increasing attention as a substitute for wheat flour in bread formulations due to immuno-nutritional features. This growing interest in quinoa has increased the demand and consequently the prices, being a target for possible adulterations with cheaper cereals. Fourier transform Mid-infrared spectroscopy (FT-MIR) was used in the present work as a fingerprinting technique to detect the presence of three adulterants (soybean, maize and wheat flours). Partial least squares discriminant analysis (PLS-DA) and soft independent modelling of class analogy (SIMCA) models were used to classify pure from adulterated samples. 414 samples were measured, including pure quinoa flour, pure adulterant flours and adulterated quinoa flours using three different proportions (10, 5 and 1% w/w). PLS-DA showed better classification results than SIMCA, with error rates from 2 to 8% for the three strategies used to detect the presence of adulterants.