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| Acceso al texto completo restringido a Biblioteca INIA Treinta y Tres. Por información adicional contacte bibliott@inia.org.uy. |
Registro completo
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Biblioteca (s) : |
INIA Treinta y Tres. |
Fecha : |
28/03/2016 |
Actualizado : |
24/09/2018 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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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INIA Treinta y Tres (TT) |
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| Acceso al texto completo restringido a Biblioteca INIA La Estanzuela. Por información adicional contacte bib_le@inia.org.uy. |
Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
Fecha actual : |
08/09/2014 |
Actualizado : |
07/11/2019 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Circulación / Nivel : |
A - 2 |
Autor : |
CASTRO A.; GAMBA, F.; GERMÁN, S.; GONZÁLEZ, S.N.; HAYES, P.M.; PEREYRA, S.; PÉREZ, C. |
Afiliación : |
SILVIA ELISA GERMAN FAEDO, Instituto Nacional de Investigación Agropecuaria (INIA), Uruguay; SILVANA NOEMÍ GONZÁLEZ PARODI, INIA La Estanzuela; SILVIA ANTONIA PEREYRA CORREA, Instituto Nacional de Investigación Agropecuaria (INIA), Uruguay. |
Título : |
Quantitative trait locus analysis of spot blotch and leaf rust resistance in the BCD47 × Baronesse barley mapping population. |
Fecha de publicación : |
2012 |
Fuente / Imprenta : |
Plant Breeding, v. 131, n. 2, p. 258-266, 2012. |
ISSN : |
0179-9541 |
DOI : |
10.1111/j.1439-0523.2011.01930.x |
Idioma : |
Inglés |
Notas : |
Article histoty: Received December 22, 2010/Accepted October 26, 2011. |
Contenido : |
Abstract:We studied the genetics of the resistance to leaf rust (LR) (caused by Puccinia hordei) and spot blotch (SB) (caused by Cochliobolus sativus)
in barley using a doubled-haploid population derived from the cross BCD47 · Baronesse. BCD47 has low SB severity and high susceptibility to LR, while Baronesse is susceptible to SB and has low LR severity. Resistance to both diseases is expressed at the adult plant stage. The population was phenotyped in eight field environments for SB and nine for LR. Ten quantitative trait loci (QTLs) were detected for SB. None were significant in more than three environments, and
both parents contributed resistance alleles. Five QTLs were detected for LR. The most consistent quantitative trait locus (QTL) (significant
in seven environments) was on chromosome 6H (located on the Bmag173-Bmag009 interval) with Baronesse contributing the resistance allele. Coincident QTL effects for SB were also detected in this region with resistance alleles to the two diseases in repulsion. These results illustrate the difficulties of resistance gene detection in the complex disease environments found under field conditions. |
Palabras claves : |
COCHLIOBOLUS SATIVUS; DISEASE RESISTANCE; HORDEUM; LEAF RUST; PUCCINIA HORDEI; QUANTITATIVE TRAIT LOCI; SPOT BLOTCH. |
Thesagro : |
FITOPATOLOGIA. |
Asunto categoría : |
H20 Enfermedades de las plantas |
Marc : |
LEADER 02163naa a2200325 a 4500 001 1050040 005 2019-11-07 008 2012 bl uuuu u00u1 u #d 022 $a0179-9541 024 7 $a10.1111/j.1439-0523.2011.01930.x$2DOI 100 1 $aCASTRO A. 245 $aQuantitative trait locus analysis of spot blotch and leaf rust resistance in the BCD47 × Baronesse barley mapping population.$h[electronic resource] 260 $c2012 500 $aArticle histoty: Received December 22, 2010/Accepted October 26, 2011. 520 $aAbstract:We studied the genetics of the resistance to leaf rust (LR) (caused by Puccinia hordei) and spot blotch (SB) (caused by Cochliobolus sativus) in barley using a doubled-haploid population derived from the cross BCD47 · Baronesse. BCD47 has low SB severity and high susceptibility to LR, while Baronesse is susceptible to SB and has low LR severity. Resistance to both diseases is expressed at the adult plant stage. The population was phenotyped in eight field environments for SB and nine for LR. Ten quantitative trait loci (QTLs) were detected for SB. None were significant in more than three environments, and both parents contributed resistance alleles. Five QTLs were detected for LR. The most consistent quantitative trait locus (QTL) (significant in seven environments) was on chromosome 6H (located on the Bmag173-Bmag009 interval) with Baronesse contributing the resistance allele. Coincident QTL effects for SB were also detected in this region with resistance alleles to the two diseases in repulsion. These results illustrate the difficulties of resistance gene detection in the complex disease environments found under field conditions. 650 $aFITOPATOLOGIA 653 $aCOCHLIOBOLUS SATIVUS 653 $aDISEASE RESISTANCE 653 $aHORDEUM 653 $aLEAF RUST 653 $aPUCCINIA HORDEI 653 $aQUANTITATIVE TRAIT LOCI 653 $aSPOT BLOTCH 700 1 $aGAMBA, F. 700 1 $aGERMÁN, S. 700 1 $aGONZÁLEZ, S.N. 700 1 $aHAYES, P.M. 700 1 $aPEREYRA, S. 700 1 $aPÉREZ, C. 773 $tPlant Breeding$gv. 131, n. 2, p. 258-266, 2012.
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