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    Título
    Prediction of fatty acid and mineral composition of lentils using near infrared spectroscopy
    Autor(es)
    Lastras, C.
    Vivar Quintana, Ana MaríaAutoridad USAL ORCID
    González Martín, María InmaculadaAutoridad USAL ORCID
    Revilla Martín, IsabelAutoridad USAL ORCID
    Palabras clave
    Legumes
    Omega-3
    Omega 6
    Calcium
    Iron
    Magnesium
    PUFAs
    Linoleic acid
    NIR
    Legumbres
    Calcio
    Hierro
    Magnesio
    Ácido linoleico
    Clasificación UNESCO
    2302.11 Ácidos grasos
    Fecha de publicación
    2021
    Editor
    Elsevier
    Citación
    Lastras, C., Revilla, I., González-Martín, M. I., & Vivar-Quintana, A. M. (2021). Prediction of fatty acid and mineral composition of lentils using near infrared spectroscopy. Journal of Food Composition and Analysis, 102, 104023. doi:10.1016/j.jfca.2021.104023
    Resumen
    [EN] Lentils are an important source of both macro- and micronutrients. Their fat content is relatively low and is composed of mainly polyunsaturated fatty acids. The minerals found in lentils are mainly magnesium, potassium and iron. This study investigates the use of near infrared reflectance spectroscopy (NIRS) to predict the mineral content and fatty acid profile of lentil seeds (Lens culinaris Medicus). Samples (57) of brown, green, black and red lentils were analysed, and their mineral (calcium, iron and magnesium) and fatty acid contents were determined. NIR spectra for whole intact samples and after the samples were ground into powder were obtained, and the two recording methods were compared. The different compounds were predicted using the modified partial least squares regression method. The predictive models developed show excellent coefficients of determination (RSQ > 0.9) for the C 16:0, C 18:2, C 20:5n-3, C 21:0, omega 6 and calcium parameters. The results obtained reveal that it is possible to predict the fatty acid and mineral composition of lentils using near infrared spectroscopy. Furthermore, the results obtained show that the equations obtained can be applied to unknown lentil samples.
    URI
    https://hdl.handle.net/10366/159938
    ISSN
    0889-1575
    DOI
    10.1016/j.jfca.2021.104023
    Versión del editor
    https://doi.org/10.1016/j.jfca.2021.104023
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