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| 1. |  | TRUJILLO, A.I. (Dir.). Eficiencia alimenticia en bovinos de carne en pastoreo. Montevideo, UY: INIA, 2015. 45 p. (Serie FPTA-INIA; 59). Proyecto FPTA 263: "Evaluación del consumo residual de alimento como una medida de eficiencia alimenticia en bovinos de carne en pastoreo". Período de ejecución: Enero 2009-Agosto 2012.
Unidad Ejecutora: Facultad de Agronomía....| Biblioteca(s): INIA Treinta y Tres. |
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| 4. | | Marichal, M.J.; Trujillo, A.I.; Guerra, M.H.; Carriquiury, M.; Piaggio, L. Comparación de las cinéticas de liberación de N-NH3 in vitro y de la degradación ruminal del N de la urea protegida, urea y subproductos agroindustriales Agrociencia, 2009, v. 13, no. 2, p. 52-59| Biblioteca(s): INIA Tacuarembó. |
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| 7. | | Soca, P.; Berretta, V.; Gutierrez, J.P.; Franco, J.; Trujillo, A.I.; Orcasberro, R. Performance de un rodeo de cría en pastoreo de campo natural sometido a destete temprano ln: Seminario Nacional de Campo Natural, 2 : 1990 nov 15-16 : Tacuarembó Montevideo (Uruguay): Hemisferio Sur, 1990. p351-354 Participaron del Seminario : INIA, Sociedad Uruguaya de Pasturas Naturales, Facultad de Agronomía, Plan Agropecuario| Biblioteca(s): INIA La Estanzuela; INIA Tacuarembó. |
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| 8. | | BERETTA, V.; SOCA, P.; TRUJILLO, A.I.; FRANCO, J.; BENTANCUR, O.; ORCASBERRO, R. Performance de vacas Hereford sometidas a dos planos de alimentación en gestación avanzada y destete temporario a inicio de entore. ln: UNIVERSIDAD DE LA REPÚBLICA (UDELAR)/ FACULTAD DE AGRONOMÍA. JORNADA DE INVESTIGACIÓN, 9 AGOSTO, EEMAC, PAYSANDÚ, URUGUAY, 1991. Resúmenes de los trabajos presentados. Montevideo (Uruguay): Facultad de Agronomía, 1991. p. 39-43| Biblioteca(s): INIA Tacuarembó. |
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| 9. | | JORGE-SMEDING, E.; TRUJILLO, A.I.; KENEZ, A.; TALMÓN, D.; MENDOZA, A.; CANTALAPIEDRA-HIJAR, G.; CARRIQUIRY, M.; ASTESSIANO, A.L. Trade-off between animal resilience and energy use in grazing cows of two Holstein genetic strains. [Abstract]. In: Annual Meeting of the European Federation of Animal Science (EAAP), 73., Porto, Portugal, 5-8 September 2022. Book of Abstracts, 73., Session 56, Theatre 9, p.598.| Biblioteca(s): INIA Las Brujas. |
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| 10. | | SOCA, P.; CARRIQUIRY, M.; QUINTANS, G.; LÓPEZ, C.; ESPASANDÍN, A.; TRUJILLO, A.I.; MARICHAL, M.DE J.; ASTESSIANO, A.L.; PÉREZ-CLARIGET, R. Empleo del flushing y destete temporario de forma táctica para mejorar indicadores reproductivos y concentración de preñez de vacas primíparas Capítulo 3. Alternativas de manejo nutricional, control del amamantamiento y tratamientos hormonales durante el posparto. In: QUINTANS, G.; VELAZCO, J.I.; ROIG, G. (Eds.). Seminario de actualización técnica: cría vacuna. Montevideo (Uruguay): INIA, 2008. p. 120-134 (INIA Serie Técnica ; 174)| Biblioteca(s): INIA Las Brujas; INIA Tacuarembó. |
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| 11. | | Burgueño, J.; Cordoba, G.; De Grossi, A.; Laborde, D.; Orcasberro, R.; Pereira, G.; Perez, H.; Seijo, G.; Soca, P.; Trujillo, A.I. Propuesta de manejo para mejorar la eficiencia reproductiva de los rodeos de cria Montevideo (Uruguay): Asociación de Ingenieros Agrónomos del Uruguay, 1993. pIX.27-29| Biblioteca(s): INIA Las Brujas. |
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 | Acceso al texto completo restringido a Biblioteca INIA Treinta y Tres. Por información adicional contacte bibliott@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA Treinta y Tres. |
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Fecha actual : |
28/03/2016 |
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Actualizado : |
24/09/2018 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
A - 1 |
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Autor : |
BASSU, S.; BRISSON, N.; DURAND, J.L.; BOOTE, K.; LIZASO, J.; JONES, J.W.; ROSENZWEIG, C.; RUANE, A.C.; ADAM, M.; BARON, C.; BASSO, B.; BIERNATH, C.; BOOGAARD, H.; CONIJN, S.; CORBEELS, M.L; DERYNG, D.; SANTIS, G. DE; GAYLER, S.; GRASSINI, P.; HATFIELD, J.; HOEK, S.; IZAURRALDE, C.; JONGSCHAAP, R.; KEMANIAN, A.R.; KERSEBAUM, C.KIM, S-H.; KUMAR, N.; MAKOWSKI, D.; MÜLLER, C.; NENDEL, C.; PRIESACK, E.; PRAVIA, V.; SAU, F.; SHCHERBAK, I.; TAO, F.; TEXEIRA, E.; TIMLIN, D.; WAHA, K. |
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Afiliación : |
MARIA VIRGINIA PRAVIA NIN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; Department of Plant Science, The Pennsylvania State University, USA. |
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Título : |
How do various maize crop models vary in their responses to climate change factors? |
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Fecha de publicación : |
2014 |
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Fuente / Imprenta : |
Global Change Biology, 2014, v.20(7), p. 2301-2320. |
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DOI : |
10.1111/gcb.12520 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 7 June 2013 and accepted 2 December 2013, published 2014. |
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Contenido : |
Abstract:
Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania).
While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data forcalibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly 0.5 Mg ha1 per °C. Doubling [CO2] from 360 to 720 lmol mol1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information. MenosAbstract:
Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania).
While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data forcalibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly 0.5 Mg ha1 per °C. Doubling [CO2] from 360 to 720 lmol mol1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2]... Presentar Todo |
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Palabras claves : |
AGMIP; CARBON DIOXIDE; CLIMATE; CO2; GRAIN YIELD; MAIZE; MODEL INTERCOMPARISON; MODELIZACIÓN DE CULTIVOS; SIMULATION MODELS; TEMPERATURE. |
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Thesagro : |
CLIMA; DIOXIDO DE CARBONO; INCERTIDUMBRE; MAÍZ; MODELOS DE SIMULACIÓN; TEMPERATURA. |
|
Asunto categoría : |
U10 Métodos matemáticos y estadísticos |
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Marc : |
LEADER 03684naa a2200769 a 4500
001 1054517
005 2018-09-24
008 2014 bl uuuu u00u1 u #d
024 7 $a10.1111/gcb.12520$2DOI
100 1 $aBASSU, S.
245 $aHow do various maize crop models vary in their responses to climate change factors?$h[electronic resource]
260 $c2014
500 $aArticle history: Received 7 June 2013 and accepted 2 December 2013, published 2014.
520 $aAbstract: Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data forcalibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly 0.5 Mg ha1 per °C. Doubling [CO2] from 360 to 720 lmol mol1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.
650 $aCLIMA
650 $aDIOXIDO DE CARBONO
650 $aINCERTIDUMBRE
650 $aMAÍZ
650 $aMODELOS DE SIMULACIÓN
650 $aTEMPERATURA
653 $aAGMIP
653 $aCARBON DIOXIDE
653 $aCLIMATE
653 $aCO2
653 $aGRAIN YIELD
653 $aMAIZE
653 $aMODEL INTERCOMPARISON
653 $aMODELIZACIÓN DE CULTIVOS
653 $aSIMULATION MODELS
653 $aTEMPERATURE
700 1 $aBRISSON, N.
700 1 $aDURAND, J.L.
700 1 $aBOOTE, K.
700 1 $aLIZASO, J.
700 1 $aJONES, J.W.
700 1 $aROSENZWEIG, C.
700 1 $aRUANE, A.C.
700 1 $aADAM, M.
700 1 $aBARON, C.
700 1 $aBASSO, B.
700 1 $aBIERNATH, C.
700 1 $aBOOGAARD, H.
700 1 $aCONIJN, S.
700 1 $aCORBEELS, M.L
700 1 $aDERYNG, D.
700 1 $aSANTIS, G. DE
700 1 $aGAYLER, S.
700 1 $aGRASSINI, P.
700 1 $aHATFIELD, J.
700 1 $aHOEK, S.
700 1 $aIZAURRALDE, C.
700 1 $aJONGSCHAAP, R.
700 1 $aKEMANIAN, A.R.
700 1 $aKERSEBAUM, C.KIM, S-H.
700 1 $aKUMAR, N.
700 1 $aMAKOWSKI, D.
700 1 $aMÜLLER, C.
700 1 $aNENDEL, C.
700 1 $aPRIESACK, E.
700 1 $aPRAVIA, V.
700 1 $aSAU, F.
700 1 $aSHCHERBAK, I.
700 1 $aTAO, F.
700 1 $aTEXEIRA, E.
700 1 $aTIMLIN, D.
700 1 $aWAHA, K.
773 $tGlobal Change Biology, 2014$gv.20(7), p. 2301-2320.
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