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Registro completo
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Biblioteca (s) : |
INIA Las Brujas; INIA Tacuarembó. |
Fecha : |
28/09/2015 |
Actualizado : |
21/02/2018 |
Tipo de producción científica : |
Capítulo en Libro Técnico-Científico |
Autor : |
DE BARBIERI, I.; MONTOSSI, F.; BERRETTA, E.; RISSO, D.; CUADRO, R.; DIGHIERO, A.; URRESTARAZÚ, A.; NOLLA, M.; LUZARDO, S.; MEDEROS, A.; MARTINEZ, H.; ZAMIT, W.; LEVRATTO, J.; BENTANCURT, M.; GARÍN, M.; ZARZA, A.; PRESA, O. |
Afiliación : |
LUIS IGNACIO DE BARBIERI ETCHEBERRY, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FABIO MARCELO MONTOSSI PORCHILE, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ELBIO JOAQUIN BERRETTA CARVALLO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; DIEGO FERNANDO RISSO RIET, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; WASHINGTON ROBIN CUADRO LOPEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ALEJANDRO DIGHIERO FASCIOLI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; A. URRESTARAZÚ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARTIN ANDRES NOLLA LAFRANCONI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SANTIAGO FELIPE LUZARDO VILLAR, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; AMERICA ESTHER MEDEROS SILVEIRA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; HOMERO MARTINEZ FORMOSO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; WILFREDO SHAMIL ZAMIT DUARTE, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JUAN CARLOS LEVRATTO CORTES, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MAURO ANDRES BENTANCURT PONTTI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; M. GARÍN, SUL (Secretariado Uruguayo de la Lana).; A. ZARZA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; OROSILDO RODOLFO PRESA SEMPER, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
XIX. Alternativas de manejo y alimentación para la producción de lanas finas y superfinas en la región de basalto. |
Fecha de publicación : |
2007 |
Fuente / Imprenta : |
ln: MONTOSSI, F.; DE BARBIERI, I. (Eds). Proyecto Merino Fino del Uruguay: una visión con perspectiva histórica. Montevideo (Uruguay): INIA, 2007. |
Páginas : |
p.207-225 |
Serie : |
(INIA Boletín de Divulgación ; 90) |
ISBN : |
978-9974-38-237-4 |
ISSN : |
1510-7396 |
Idioma : |
Español |
Palabras claves : |
LANAS FINAS; LANAS ULTRAFINAS. |
Thesagro : |
LANA; MERINO; MERINO FINO; PRODUCCION DE LANA. |
Asunto categoría : |
L10 Genética y mejoramiento animal |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/8725/1/Bd-90-p.-207-225.pdf
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Marc : |
LEADER 01230naa a2200421 a 4500 001 1053424 005 2018-02-21 008 2007 bl uuuu u00u1 u #d 020 $a978-9974-38-237-4 022 $a1510-7396 100 1 $aDE BARBIERI, I. 245 $aXIX. Alternativas de manejo y alimentación para la producción de lanas finas y superfinas en la región de basalto. 260 $c2007 300 $ap.207-225 490 $a(INIA Boletín de Divulgación ; 90) 650 $aLANA 650 $aMERINO 650 $aMERINO FINO 650 $aPRODUCCION DE LANA 653 $aLANAS FINAS 653 $aLANAS ULTRAFINAS 700 1 $aMONTOSSI, F. 700 1 $aBERRETTA, E. 700 1 $aRISSO, D. 700 1 $aCUADRO, R. 700 1 $aDIGHIERO, A. 700 1 $aURRESTARAZÚ, A. 700 1 $aNOLLA, M. 700 1 $aLUZARDO, S. 700 1 $aMEDEROS, A. 700 1 $aMARTINEZ, H. 700 1 $aZAMIT, W. 700 1 $aLEVRATTO, J. 700 1 $aBENTANCURT, M. 700 1 $aGARÍN, M. 700 1 $aZARZA, A. 700 1 $aPRESA, O. 773 $tln: MONTOSSI, F.; DE BARBIERI, I. (Eds). Proyecto Merino Fino del Uruguay: una visión con perspectiva histórica. Montevideo (Uruguay): INIA, 2007.
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INIA Las Brujas (LB) |
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Registro completo
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Biblioteca (s) : |
INIA Treinta y Tres. |
Fecha actual : |
28/03/2016 |
Actualizado : |
24/09/2018 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Circulación / Nivel : |
A - 1 |
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. |
Afiliación : |
MARIA VIRGINIA PRAVIA NIN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; Department of Plant Science, The Pennsylvania State University, USA. |
Título : |
How do various maize crop models vary in their responses to climate change factors? |
Fecha de publicación : |
2014 |
Fuente / Imprenta : |
Global Change Biology, 2014, v.20(7), p. 2301-2320. |
DOI : |
10.1111/gcb.12520 |
Idioma : |
Inglés |
Notas : |
Article history: Received 7 June 2013 and accepted 2 December 2013, published 2014. |
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 |
Palabras claves : |
AGMIP; CARBON DIOXIDE; CLIMATE; CO2; GRAIN YIELD; MAIZE; MODEL INTERCOMPARISON; MODELIZACIÓN DE CULTIVOS; SIMULATION MODELS; TEMPERATURE. |
Thesagro : |
CLIMA; DIOXIDO DE CARBONO; INCERTIDUMBRE; MAÍZ; MODELOS DE SIMULACIÓN; TEMPERATURA. |
Asunto categoría : |
U10 Métodos matemáticos y estadísticos |
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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