Fecha/hora: 31/05/2024 22:10:31

Biblioteca(s): | INIA Las Brujas.
Fecha corriente: | 22/11/2016
Fecha de la última actualización: | 22/11/2016
Autoria: | COZZOLINO, D.; FASSIO, A.; RESTAINO, E.; FERNANDEZ, E.; LA MANNA, A.
Afiliación: | DANIEL COZZOLINO GÓMEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ALBERTO SANTIAGO FASSIO ARAUJO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ERNESTO ANGEL RESTAINO GALUP, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ENRIQUE GENARO FERNANDEZ RODRIGUEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ALEJANDRO FRANCISCO LA MANNA ALONSO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay.
Título: | Verification of silage type using near-infrared spectroscopy combined with multivariate analysis.
Año de publicación: | 2008
Fuente/Imprenta: | Journal of Agricultural and Food Chemistry, 2008, v. 56, no.1, p.79-83.
DOI: | 10.1021/jf072566d
Idioma: | Inglés
Notas: | Received 28 August 2007 // Date accepted 8 November 2007 // Published online 27 November 2007 // Published in print 1 January 2008.

Contenido:

ABSTRACT.

The ability to authenticate the feed given to animals has become a major challenge in animal production, where the diet fed to the animal is one of the most important production factors affecting the composition of milk and meat from cattle, sheep, and goats. Hence, there is currently an increased consumer demand for information on herbivore production factors and particularly the animal diet. The aim of this study was to evaluate the reliability and accuracy of near-infrared (NIR) reflectance spectroscopy as a tool to verify and authenticate the type of silage used as fed for ruminants. Grain silage (GrS, n ) 94), grass and legume silage (GLegS, n ) 121), and sunflower silage (SunS, n ) 50) samples were collected from commercial farms and analyzed in the visible and NIR regions (400-2500 nm) in a monochromator instrument in reflectance. Principal component analysis (PCA), 
partial least-squares discriminant analysis (PLS1-DA), and linear discriminant analysis (LDA) models  ere used as methods to verify the different silage types. The classification models based on the NIR data correctly classified more than 90% of the silage samples according to their type. The results from this study showed that NIR spectra combined with multivariate analysis could be used as a tool to objectively authenticate silage samples used as a feed for ruminants.

© 2008 American Chemical Society

Palabras-Clave: | IDENTIFICATION; LINEAR DISCRIMINANT ANALYSIS; NEAR-INFRARED SPECTROSCOPY; PARTIAL LEAST-SQUARES DISCRIMINANT ANALYSIS; PRINCIPAL COMPONENT ANALYSIS; SILAGE.
Categoría del tema: | --
Registro original: | INIA Las Brujas (LB)
Ejemplares: | LB - (101239-1) - PXI - AP - DD - PP/JR.AGR.FOOD CHEM./ -  -  - DIS