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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
18/03/2021 |
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Actualizado : |
22/03/2021 |
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Tipo de producción científica : |
Abstracts/Resúmenes |
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Autor : |
FERNANDEZ, E.; SOARES DE LIMA, J.M.; FERRARO, B.; LANFRANCO, B. |
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Afiliación : |
ENRIQUE GENARO FERNANDEZ RODRIGUEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JUAN MANUEL SOARES DE LIMA LAPETINA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; BRUNO FERRARO ALBERTONI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; BRUNO ANTONIO LANFRANCO CRESPO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Modellng alternative technology adoption transformation scenarios to achieve production and economic performance goals in the uruguayan beef cattle sector. [abstract + poster] |
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Fecha de publicación : |
2019 |
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Fuente / Imprenta : |
In: International Conference on Food and Agricultural Economics, 3., ECONAGRO, 2019, Alanya, Turkey. Proceedings book. p.53-54. |
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ISBN : |
978-605-81058-1-2 |
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Idioma : |
Inglés |
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Notas : |
Editado por: Harun Uçak (Ed.). Alanya Alaaddin Keykubat University. 3rd International Conference on Food and Agricultural Economics. ECONAGRO. Proceeding Book.
25 -26th April 2019 Alanya Alaaddin Keykubat University, Turkey. |
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Contenido : |
Abtract.
The Agricultural Transformation Pathways (ATP) for Uruguay and two other selected study cases issued in 2016 in the frame of the UN´s Sustainable Development Solutions Network (SDSN) projectmade relevant advances in setting the desired and feasible goals and development objectives for 2030 (Schwoob et al., 2016). Beef is one of the main agri-food chains included in Uruguay´s first studies given is the country´s main export and production is the largest in terms of land used (12,6
million ha) and farms involved (44780).
Understanding the relationship among the multiple factors driving farmers´ decision making process is crucial for policymakers and experts selecting the best pathway to overcome roadblocks and reach goals. This paper addresses the relationship between farm business orientation, farm size, technological level, production performance and economic return in the beef cattle production sector. The objective is to understand the main constraints to the adoption of technology and the main factors to consider in the design of future assistance programs. |
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Palabras claves : |
Livestock Production Modeling; Meat; SDSN; Sustainable Intensification; Technology Adoption; UNIDAD ECONOMIA APLICADA - INIA. |
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Asunto categoría : |
E10 Economía y políticas agrícolas |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/15359/1/Fernandez-Soares-de-Lima-Ferraro-Lanfranco.-ECONAGRO-2019-Proceedings.pdf
http://www.ainfo.inia.uy/digital/bitstream/item/15373/1/Poster-Ravello-236.pdf
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Marc : |
LEADER 02211nam a2200241 a 4500
001 1061840
005 2021-03-22
008 2019 bl uuuu u01u1 u #d
020 $a978-605-81058-1-2
100 1 $aFERNANDEZ, E.
245 $aModellng alternative technology adoption transformation scenarios to achieve production and economic performance goals in the uruguayan beef cattle sector. [abstract + poster]$h[electronic resource]
260 $aIn: International Conference on Food and Agricultural Economics, 3., ECONAGRO, 2019, Alanya, Turkey. Proceedings book. p.53-54.$c2019
500 $aEditado por: Harun Uçak (Ed.). Alanya Alaaddin Keykubat University. 3rd International Conference on Food and Agricultural Economics. ECONAGRO. Proceeding Book. 25 -26th April 2019 Alanya Alaaddin Keykubat University, Turkey.
520 $aAbtract. The Agricultural Transformation Pathways (ATP) for Uruguay and two other selected study cases issued in 2016 in the frame of the UN´s Sustainable Development Solutions Network (SDSN) projectmade relevant advances in setting the desired and feasible goals and development objectives for 2030 (Schwoob et al., 2016). Beef is one of the main agri-food chains included in Uruguay´s first studies given is the country´s main export and production is the largest in terms of land used (12,6 million ha) and farms involved (44780). Understanding the relationship among the multiple factors driving farmers´ decision making process is crucial for policymakers and experts selecting the best pathway to overcome roadblocks and reach goals. This paper addresses the relationship between farm business orientation, farm size, technological level, production performance and economic return in the beef cattle production sector. The objective is to understand the main constraints to the adoption of technology and the main factors to consider in the design of future assistance programs.
653 $aLivestock Production Modeling
653 $aMeat
653 $aSDSN
653 $aSustainable Intensification
653 $aTechnology Adoption
653 $aUNIDAD ECONOMIA APLICADA - INIA
700 1 $aSOARES DE LIMA, J.M.
700 1 $aFERRARO, B.
700 1 $aLANFRANCO, B.
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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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