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Análisis del contenido en minerales en nabizas y grelos (Brassica rapaL. var.rapa) mediante reflectancia en el infrarrojo cercano

Authors: Obregón Cano, Sara; Moreno Rojas, Rafael; Jurado-Millán, A.M.; Haro Bailón, Antonio de;

Análisis del contenido en minerales en nabizas y grelos (Brassica rapaL. var.rapa) mediante reflectancia en el infrarrojo cercano

Abstract

The objective of this study was to evaluate the potential and accuracy of near-infrared reflectance spectroscopy (NIRS) for predicting the mineral content in lyophilized samples of turnip greens and turnip tops (Brassica rapa L. var. rapa). Mathematical treatments of the spectra and modified partial least squares regression (MPLS) were used for developing calibrations equations (n = 298). An independent set of samples (n = 69) was used to evaluate and validate the performance of the calibrations equations. The coefficients of determination obtained in the external validation (r2 ev) and error of prediction (SEP) for the different minerals were K = 0.86 (SEP = 4,90), Ca = 0.91 (SEP = 1,66), P = 0.73 (SEP = 0,86), Mg = 0.85 (SEP = 0,32), Na = 0.87 (SEP = 0,21), Fe = 0.90 (SEP = 60,48), Zn = 0.80 (SEP = 5,83), Mn = 0.81 (SEP = 5,72) and Cu = 0.62 (SEP = 1,13).The calibration equations obtained for Ca and Fe showed the highest predictive ability These results support the idea that NIRS technology is suitable for the fast, non-destructive, and accurate prediction of mineral content in turnip greens and turnip tops.

El objetivo de este trabajo fue la evaluación del potencial de la espectroscopía de reflectancia en el infrarrojo cercano (NIRS) para el análisis del contenido mineral en muestras liofilizadas de nabizas y grelos (Brassica rapa L. var. rapa). Se aplicó el método de mínimos cuadrados parciales modificados (MPLS) para desarrollar ecuaciones de calibración (n=298). Se evaluó la capacidad predictiva de las ecuaciones de calibración obtenidas mediante un lote de muestras (n=69) independientes del colectivo de calibración. Los coeficientes de determinación (r2 ve) y errores de predicción (SEP) obtenidos en la validación externa para los distintos minerales fueron K=0,86(SEP=4,90); Ca=0,91 (SEP=1,66); P=0,73(SEP=0,86); Mg=0,85(SEP=0,32); Na=0,87(SEP=0,21); Fe=0,90(SEP=60,48); Zn=0,80(SEP=5,83); Mn=0,81 (SEP=5,72)y Cu=0,62(SEP=1,13). Las ecuaciones para Ca y Fe fueron las que mostraron mayor capacidad predictiva. Estos resultados demuestran el potencial del NIRS para el análisis rápido, no destructivo y preciso del contenido mineral en nabizas y grelos.

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Spain
Keywords

Manganese, Iron, Brassica rapa, Sodium, Phosphorus, Manganeso, Magnesio, Zinc, Calcio, Cobre, NIRS, Sodio, Potassium, Fósforo, Calcium, Magnesium, Potasio, Copper, Hierro

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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