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![](/consulta/web/img/deny.png) | Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
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Biblioteca (s) : |
INIA Las Brujas. |
Fecha : |
17/11/2023 |
Actualizado : |
17/11/2023 |
Tipo de producción científica : |
Poster |
Autor : |
NAVAJAS, E.; CIAPPESONI, G.; DE BARBIERI, I. |
Afiliación : |
ELLY ANA NAVAJAS VALENTINI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; CARLOS GABRIEL CIAPPESONI SCARONE, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; LUIS IGNACIO DE BARBIERI ETCHEBERRY, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Contrasting genetic resistance to GIN on growth performance ancl feed efficiency of Corriedale lambs. [Poster. Session 96, Theatre 9]. |
Complemento del título : |
Conference Proceedings. |
Fecha de publicación : |
2023 |
Fuente / Imprenta : |
In: Annual Meeting of the European Federation of Animal Science (EAAP), 74., Lyon, France, August 26 - September 1 2023. Book of Abstracts, Volume 29: Pp. 1037. doi: https://doi.org/10.3920/978-90-8686-936-7 |
ISBN : |
978-90-8686-384-6; e-ISBN: 978-90-8686-936-7 |
ISSN : |
1382-6077 |
Idioma : |
Inglés |
Notas : |
Conference website: https://eaap2023.org/ |
Contenido : |
Genetic improvement of resistance to gastrointestinal nematodes (GIN) in sheep is a well-known strategy to reduce the negative consequences of GIN, whose control is limitecl by resistance to anthehnintics, on sheep health and performance. |
Palabras claves : |
Animal genetics; Sheep. |
Asunto categoría : |
-- |
Marc : |
LEADER 01010nam a2200181 a 4500 001 1064373 005 2023-11-17 008 2023 bl uuuu u00u1 u #d 022 $a1382-6077 100 1 $aNAVAJAS, E. 245 $aContrasting genetic resistance to GIN on growth performance ancl feed efficiency of Corriedale lambs. [Poster. Session 96, Theatre 9].$h[electronic resource] 260 $aIn: Annual Meeting of the European Federation of Animal Science (EAAP), 74., Lyon, France, August 26 - September 1 2023. Book of Abstracts, Volume 29: Pp. 1037. doi: https://doi.org/10.3920/978-90-8686-936-7$c8686 500 $aConference website: https://eaap2023.org/ 520 $aGenetic improvement of resistance to gastrointestinal nematodes (GIN) in sheep is a well-known strategy to reduce the negative consequences of GIN, whose control is limitecl by resistance to anthehnintics, on sheep health and performance. 653 $aAnimal genetics 653 $aSheep 700 1 $aCIAPPESONI, G. 700 1 $aDE BARBIERI, I.
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![](/consulta/web/img/deny.png) | 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 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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