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BASADAS EN ADN PARA EL ANÁLISIS DE LAS COMUNIDADES DE MICROORGANISMOS Y CIANOBACTERIAS DEL SEDIMENTO EN EL EMBALSE RINCÓN DEL BONETE- URUGUAY In: REDBIO México 2022, XI Congreso, "Biotecnología productiva y sostenible". Libro de resúmenes. 12-14 octubre 2022, Yucatán, México. p.127. Agradecimientos: A los Institutos INIA y LATU con sus respectivas autoridades por la cofinanciación del Proyecto: "Desarrollo y Aplicación de nuevas herramientas moleculares y espectrales para el estudio de las comunidades de...Biblioteca(s): INIA Las Brujas. |
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80. | | DEVINCENZI, T.; JAURENA, M.; DURANTE, M.; SAVIAN, J.V.; CIAPPESONI, G.; NAVAJAS, E.; CIGANDA, V.; LATTANZI, F.; PARUELO, J. Building the GLENCOE Platform -Grasslands LENding eConomic and ecOsystems sErvices. Frontiers in Sustainable Food Systems, June 2021, volume 516, Article 547301. OPEN ACCESS. Doi: https://doi.org/10.3389/fsufs.2021.547301 Article history: Received 31 March 2020, Accepted 26 April 2021, Published 16 June 2021.
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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
Fecha actual : |
21/02/2014 |
Actualizado : |
01/10/2019 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Circulación / Nivel : |
B - 1 |
Autor : |
COZZOLINO, D.; VAZ MARTINS, D.; MURRAY, I, |
Afiliación : |
DANIEL COZZOLINO GÓMEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; DANIEL VAZ MARTINS GIGENA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; Animal Biology Division, Ferguson Building, Scottish Agricultural College, Craibstone State, Aberdeen AB21 9YA, UK. |
Título : |
Visible and near infrared spectroscopy of beef longissimus dorsi muscle as a means of dicriminating between pasture and corn silage feeding regimes. |
Fecha de publicación : |
2002 |
Fuente / Imprenta : |
Journal of Near Infrared Spectroscopy, 2002, Volume 10, Issue 3, Pages 187-193 |
DOI : |
10.1255/jnirs.334 |
Idioma : |
Inglés |
Notas : |
Article history:Received: October 09, 2001/ Accepted: May 14, 2002/Revisions received: March 19, 2002. |
Contenido : |
Abstract:
Near infrared (NIR) reflectance spectroscopy was used as a tool to classify beef muscle samples according to their feeding regime. Seventy-eight beef longissimus dorsi muscle samples both intact and minced were scanned in a NIRS 6500 instrument (NIRSystems, MD, USA) in reflectance. A dummy regression technique was developed to differentiate beef muscle samples, which originated from beef feed exclusively on pasture or/and mainly on corn silage feeding regimes. Ninety percent of the pasture-fed beef muscle samples were correctly classified using principal component regression (PCR) and 86% of beef fed on corn silage were correctly classified. Both muscle chemical composition and physical characteristics explained the classification results. The results in the present study showed the potential of muscle optical properties for classification and traceability of meat muscles in the food chain. |
Palabras claves : |
CORN SILAGE; MEAT; NEAR INFRARED REFLECTANCE SPECTROSCOPY; ORIGIN; PASTURES. |
Thesagro : |
NIRS. |
Asunto categoría : |
-- |
Marc : |
LEADER 01776naa a2200241 a 4500 001 1035310 005 2019-10-01 008 2002 bl uuuu u00u1 u #d 024 7 $a10.1255/jnirs.334$2DOI 100 1 $aCOZZOLINO, D. 245 $aVisible and near infrared spectroscopy of beef longissimus dorsi muscle as a means of dicriminating between pasture and corn silage feeding regimes.$h[electronic resource] 260 $c2002 500 $aArticle history:Received: October 09, 2001/ Accepted: May 14, 2002/Revisions received: March 19, 2002. 520 $aAbstract: Near infrared (NIR) reflectance spectroscopy was used as a tool to classify beef muscle samples according to their feeding regime. Seventy-eight beef longissimus dorsi muscle samples both intact and minced were scanned in a NIRS 6500 instrument (NIRSystems, MD, USA) in reflectance. A dummy regression technique was developed to differentiate beef muscle samples, which originated from beef feed exclusively on pasture or/and mainly on corn silage feeding regimes. Ninety percent of the pasture-fed beef muscle samples were correctly classified using principal component regression (PCR) and 86% of beef fed on corn silage were correctly classified. Both muscle chemical composition and physical characteristics explained the classification results. The results in the present study showed the potential of muscle optical properties for classification and traceability of meat muscles in the food chain. 650 $aNIRS 653 $aCORN SILAGE 653 $aMEAT 653 $aNEAR INFRARED REFLECTANCE SPECTROSCOPY 653 $aORIGIN 653 $aPASTURES 700 1 $aVAZ MARTINS, D. 700 1 $aMURRAY, I, 773 $tJournal of Near Infrared Spectroscopy, 2002, Volume 10, Issue 3, Pages 187-193
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