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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela; INIA Las Brujas; INIA Tacuarembó; INIA Treinta y Tres. |
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Fecha : |
10/07/2015 |
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Actualizado : |
30/10/2019 |
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Tipo de producción científica : |
Serie Técnica |
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Autor : |
OLMOS, F.; SOSA, M.; SALVARREY, L.; CARDOZO, G.; SOARES DE LIMA, J.M.; GIORELLO, D.; VIÑOLES, C.; MONTOSSI, F. |
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Afiliación : |
FERNANDO ELCEAR OLMOS LOPEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARTIN OSORIO SOSA PINTADO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; LUIS SALVARREY, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; GERONIMO AGUSTIN CARDOZO CABANELAS, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JUAN MANUEL SOARES DE LIMA LAPETINA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; DIEGO GERMAN GIORELLO LEITES, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; CAROLINA VIÑOLES GIL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FABIO MARCELO MONTOSSI PORCHILE, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Productividad de pasturas estivales en la región Noreste. |
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Fecha de publicación : |
2015 |
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Fuente / Imprenta : |
Montevideo, UY: INIA, 2015. |
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Páginas : |
94 p. |
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Serie : |
(Serie Técnica, 222). |
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ISSN : |
1688-9266 |
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DOI : |
http://doi.org/10.35676/INIA/ST.222 |
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Idioma : |
Español |
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Contenido : |
En esta publicación se presentan distintos trabajos realizados en la región noreste con algunas de las especies forrajeras estivales más promisorias desde el punto de vista de su productividad y así como su respuesta al manejo de variables agronómicas como los niveles de fertilización, la frecuencia de corte, el método de siembra, la asociación con leguminosas, como una contribución a la realización de los balances forrajeros estacionales para sistemas ganaderos de cría y ciclo completo. |
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Palabras claves : |
CANUTILLO; CYNODON TIFTON 85; ENTORE PRECOZ; MODELO CONCEPTUAL PARA LA GANADERÍA EXTENSIVA; PASPALUM CHIRÚ; PASTURAS ESTIVALES; PENNISETUM AMERICANUM; RECRÍA DE TERNERAS; REGIÓN NORESTE (URUGUAY); TERNERAS PARA CARNE. |
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Thesagro : |
ANDROPOGON LATERALIS; CHLORIS GAYANA; CYNODON DACTYLON; LOTUS CORNICULATUS; PASPALUM DILATATUM; PASTO ITALIANO; PRODUCCIÓN DE FORRAJES; PRODUCCIÓN DE SEMILLAS; SETARIA SPHACELATA. |
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Asunto categoría : |
--
F01 Cultivo |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/4847/1/st-222-2015.pdf
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Marc : |
LEADER 01826nam a2200469 a 4500
001 1053096
005 2019-10-30
008 2015 bl uuuu u00u1 u #d
022 $a1688-9266
024 7 $ahttp://doi.org/10.35676/INIA/ST.222$2DOI
100 1 $aOLMOS, F.
245 $aProductividad de pasturas estivales en la región Noreste.
260 $aMontevideo, UY: INIA$c2015
300 $a94 p.
490 $a(Serie Técnica, 222).
520 $aEn esta publicación se presentan distintos trabajos realizados en la región noreste con algunas de las especies forrajeras estivales más promisorias desde el punto de vista de su productividad y así como su respuesta al manejo de variables agronómicas como los niveles de fertilización, la frecuencia de corte, el método de siembra, la asociación con leguminosas, como una contribución a la realización de los balances forrajeros estacionales para sistemas ganaderos de cría y ciclo completo.
650 $aANDROPOGON LATERALIS
650 $aCHLORIS GAYANA
650 $aCYNODON DACTYLON
650 $aLOTUS CORNICULATUS
650 $aPASPALUM DILATATUM
650 $aPASTO ITALIANO
650 $aPRODUCCIÓN DE FORRAJES
650 $aPRODUCCIÓN DE SEMILLAS
650 $aSETARIA SPHACELATA
653 $aCANUTILLO
653 $aCYNODON TIFTON 85
653 $aENTORE PRECOZ
653 $aMODELO CONCEPTUAL PARA LA GANADERÍA EXTENSIVA
653 $aPASPALUM CHIRÚ
653 $aPASTURAS ESTIVALES
653 $aPENNISETUM AMERICANUM
653 $aRECRÍA DE TERNERAS
653 $aREGIÓN NORESTE (URUGUAY)
653 $aTERNERAS PARA CARNE
700 1 $aSOSA, M.
700 1 $aSALVARREY, L.
700 1 $aCARDOZO, G.
700 1 $aSOARES DE LIMA, J.M.
700 1 $aGIORELLO, D.
700 1 $aVIÑOLES, C.
700 1 $aMONTOSSI, F.
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Registro original : |
INIA Las Brujas (LB) |
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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. |
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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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