Fecha/hora: 08/06/2024 05:51:56

Biblioteca(s): 	INIA La Estanzuela.	
Fecha corriente: 	21/02/2014	
Fecha de la última actualización: 	30/09/2019	
Autoria: 	COZZOLINO, D.; MORON, A.	
Afiliación: 	DANIEL COZZOLINO GÓMEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; DAVID ALEJANDRO MORON YACOEL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay.	
Título: 	Exploring the use of near infrared reflectance spectroscopy (NIRS) to predict trace minerals in legumes.	
Año de publicación: 	2004	
Fuente/Imprenta: 	Animal Feed Science and Technology, Volume 111, Issues 1?4, 12 January 2004, Pages 161-173.	
DOI: 	10.1016/j.anifeedsci.2003.08.001	
Idioma: 	Inglés	
Notas: 	Article history: Received 28 January 2003 / Received in revised form 23 July 2003 / Accepted 5 August 2003.	
Contenido: 	Abstract:
The use of near infrared reflectance spectroscopy (NIRS) was explored to predict trace mineral concentrations in two legumes. Samples (332), composite of white clover (n=97) and lucerne (n=235), from different locations in Uruguay representing a wide range of soil types, were analysed for sodium (Na), sulphur (S), copper (Cu), iron (Fe), manganese (Mn), zinc (Zn), and boron (B). The samples were scanned in reflectance in a monochromator instrument (400?2500 nm). Calibration models (n=262) were developed using modified partial least squares regression (MPLS) based on cross-validation and tested using a validation set (n=70). Two mathematical treatments of the spectra were compared (first and second derivative). The highest coefficients of determination in calibration (RCAL2) and the lowest standard errors of cross-validation (SECV) were obtained using second derivative. The RCAL2 and SECV were 0.83 (SECV: 0.8) for Na and 0.86 (SECV: 2.5) for S in g kg?1 DM; 0.80 (SECV: 4.4), 0.80 (SECV: 10.6), 0.78 (SECV: 22.9), 0.76 (SECV: 0.83) and 0.57 (SECV 25.7) for B, Zn, Mn, Cu and Fe in mg kg?1 DM on a dry weight, respectively. Sulphur (SEP: 5.5), sodium (SEP: 1.2) and boron (SEP 4.2) were well predicted by NIRS on a validation set.	
Palabras-Clave: 	LEGUMES FORAGE QUALITY; NIRS; PARTIAL LEAST SQUARES; TRACE MINERALS.	
Categoría del tema: 	--	
Registro original: 	INIA La Estanzuela (LE)	
Ejemplares: 	LE - (49567-1) - PXI - AP - PP - PP/Animal FST/2004 -  -  - DIS