Prediction of fatty acid and mineral composition of lentils using near infrared spectroscopy
[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 spec...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universidad de Salamanca (USAL) |
| Repositorio: | GREDOS. Repositorio Institucional de la Universidad de Salamanca |
| OAI Identifier: | oai:gredos.usal.es:10366/159938 |
| Acceso en línea: | http://hdl.handle.net/10366/159938 |
| Access Level: | acceso abierto |
| Palabra clave: | Legumes Omega-3 Omega 6 Calcium Iron Magnesium PUFAs Linoleic acid NIR Legumbres Calcio Hierro Magnesio Ácido linoleico 2302.11 Ácidos grasos |
| Sumario: | [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. |
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