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Registro completo
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Biblioteca (s) : |
INIA Tacuarembó. |
Fecha : |
21/02/2014 |
Actualizado : |
17/08/2018 |
Autor : |
BIANCHI, G. |
Afiliación : |
GIANNI BIANCHI. |
Título : |
Cómo enfrentar uno de los problemas más importantes en la faena de ovinos: la contaminación de las canales. |
Fecha de publicación : |
2010 |
Fuente / Imprenta : |
El País Agropecuario, 2010, v. 16, no. 188, p. 28-30. |
Idioma : |
Español |
Contenido : |
El problema. ¿Qué se ha realizado en Uruguay?. ¿Qué se puede hacer con la información local disponible hasta el momento? |
Palabras claves : |
CONTAMINACIÓN DE LA CANAL. |
Thesagro : |
CANAL ANIMAL; OVINOS; TRANSPORTE DE ANIMALES. |
Asunto categoría : |
L01 Ganadería |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/11025/1/188p28.pdf
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Marc : |
LEADER 00645naa a2200169 a 4500 001 1028639 005 2018-08-17 008 2010 bl uuuu u00u1 u #d 100 1 $aBIANCHI, G. 245 $aCómo enfrentar uno de los problemas más importantes en la faena de ovinos$bla contaminación de las canales. 260 $c2010 520 $aEl problema. ¿Qué se ha realizado en Uruguay?. ¿Qué se puede hacer con la información local disponible hasta el momento? 650 $aCANAL ANIMAL 650 $aOVINOS 650 $aTRANSPORTE DE ANIMALES 653 $aCONTAMINACIÓN DE LA CANAL 773 $tEl País Agropecuario, 2010$gv. 16, no. 188, p. 28-30.
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INIA Tacuarembó (TBO) |
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| Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
Fecha actual : |
22/11/2016 |
Actualizado : |
22/11/2016 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Circulación / Nivel : |
A - 1 |
Autor : |
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. |
Fecha 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 claves : |
IDENTIFICATION; LINEAR DISCRIMINANT ANALYSIS; NEAR-INFRARED SPECTROSCOPY; PARTIAL LEAST-SQUARES DISCRIMINANT ANALYSIS; PRINCIPAL COMPONENT ANALYSIS; SILAGE. |
Asunto categoría : |
-- |
Marc : |
LEADER 02371naa a2200265 a 4500 001 1056114 005 2016-11-22 008 2008 bl uuuu u00u1 u #d 024 7 $a10.1021/jf072566d$2DOI 100 1 $aCOZZOLINO, D. 245 $aVerification of silage type using near-infrared spectroscopy combined with multivariate analysis.$h[electronic resource] 260 $c2008 500 $aReceived 28 August 2007 // Date accepted 8 November 2007 // Published online 27 November 2007 // Published in print 1 January 2008. 520 $aABSTRACT. 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 653 $aIDENTIFICATION 653 $aLINEAR DISCRIMINANT ANALYSIS 653 $aNEAR-INFRARED SPECTROSCOPY 653 $aPARTIAL LEAST-SQUARES DISCRIMINANT ANALYSIS 653 $aPRINCIPAL COMPONENT ANALYSIS 653 $aSILAGE 700 1 $aFASSIO, A. 700 1 $aRESTAINO, E. 700 1 $aFERNANDEZ, E. 700 1 $aLA MANNA, A. 773 $tJournal of Agricultural and Food Chemistry, 2008$gv. 56, no.1, p.79-83.
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