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Registro completo
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Biblioteca (s) : |
INIA Las Brujas; INIA Treinta y Tres. |
Fecha : |
12/11/2015 |
Actualizado : |
09/10/2019 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Autor : |
MARCAIDA, M.; ASSENG, S.; EWERT, F.; BASSU, S.; DURAND, J.L.; LI, T.; MARTRE, P.; ADAM, M.; AGGARWAL, P.K.; ANGULO, C.; BARON, C.; BASSO, B.; BERTUZZI, P.; BIERNATH, C.; BOOGAARD, H.; BOOTE, K.J.; BOUMAN, B.; BREGAGLIO, S.; BRISSON, N.; BUIS, S.; CAMMARANO, D.; CHALLINOR, A.J.; CONFALONIERI, R.; CONIJN, J.G.; CORBEELS, M.; DERYNG, D.; DE SANCTIS, G.; DOLTRA, J.; FUMOTO, T.; GAYDON, D.; GAYLER, S.; GOLDBERG, R.; GRANT, R.F.; GRASSINI, P.; HATFIELD, J.L.; HASEGAWA, T.; HENG, L.; HOEK, S.; HOOKER, J.; HUNT, L.A.; INGWERSEN, J.; IZAURRALDE, R.C.; JONGSCHAAP, R.E.E.; JONES, J.W.; KEMANIAN, R.A.; KERSEBAUM, K.C.; KIM, S.-H.; LIZASO, J.; MÜLLER, C.; NAKAGAWA, H.; NARESH KUMAR, S.; NENDEL, C.; O'LEARY, G.J.; OLESEN, J.E.; ORIOL, P.; OSBORNE, T.M.; PALOSUO, T.; PRAVIA, V.; PRIESACK, E.; RIPOCHE, D.; ROSENZWEIG, C.; RUANE, A.C.; RUGET, F.; SAU, F.; SEMENOV, M.A.; SHCHERBAK, I.; SINGH, B.; SINGH, U.; SOO, H.K.; STEDUTO, P.; STÖCKLE, C.; STRATONOVITCH, P.; STRECK, T.; SUPIT, I.; TANG, L.; TAO, F.; TEIXEIRA, E.I.; THORBURN, P.; TIMLIN, D.; TRAVASSO, M.; RÖTTER, R.P.; WAHA, K.; WALLACH, D.; WHITE, J.W.; WILKENS, P.; WILLIAMS, J.R.; WOLF, J.; YIN, X.; YOSHIDA, H.; ZHANG, Z.; ZHU, Y. |
Afiliación : |
MARIA VIRGINIA PRAVIA NIN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration. |
Fecha de publicación : |
2015 |
Fuente / Imprenta : |
Agricultural and Forest Meteorology, 2015, v.214-215, p. 483-493. |
ISSN : |
0168-1923 |
DOI : |
10.1016/j.agrformet.2015.09.013 |
Idioma : |
Inglés |
Notas : |
Article history: Received 6 March 2015 / Received in revised form 29 July 2015 / Accepted 20 September 2015 / Available online 1 October 2015. |
Contenido : |
ABSTRACT.
Ensembles of process-based crop models are increasingly used to simulate crop growth for scenariosof temperature and/or precipitation changes corresponding to different projections of atmospheric CO2concentrations. This approach generates large datasets with thousands of simulated crop yield data. Suchdatasets potentially provide new information but it is difficult to summarize them in a useful way due totheir structural complexities. An associated issue is that it is not straightforward to compare crops and tointerpolate the results to alternative climate scenarios not initially included in the simulation protocols.Here we demonstrate that statistical models based on random-coefficient regressions are able to emulateensembles of process-based crop models. An important advantage of the proposed statistical models isthat they can interpolate between temperature levels and between CO2concentration levels, and canthus be used to calculate temperature and [CO2] thresholds leading to yield loss or yield gain, without re-running the original complex crop models. Our approach is illustrated with three yield datasets simulatedby 19 maize models, 26 wheat models, and 13 rice models. Several statistical models are fitted to thesedatasets, and are then used to analyze the variability of the yield response to [CO2] and temperature.Based on our results, we show that, for wheat, a [CO2] increase is likely to outweigh the negative effectof a temperature increase of +2◦C in the considered sites. Compared to wheat, required levels of [CO2]increase are much higher for maize, and intermediate for rice. For all crops, uncertainties in simulatingclimate change impacts increase more with temperature than with elevated [CO2].
© 2015 Elsevier B.V. All rights reserved. MenosABSTRACT.
Ensembles of process-based crop models are increasingly used to simulate crop growth for scenariosof temperature and/or precipitation changes corresponding to different projections of atmospheric CO2concentrations. This approach generates large datasets with thousands of simulated crop yield data. Suchdatasets potentially provide new information but it is difficult to summarize them in a useful way due totheir structural complexities. An associated issue is that it is not straightforward to compare crops and tointerpolate the results to alternative climate scenarios not initially included in the simulation protocols.Here we demonstrate that statistical models based on random-coefficient regressions are able to emulateensembles of process-based crop models. An important advantage of the proposed statistical models isthat they can interpolate between temperature levels and between CO2concentration levels, and canthus be used to calculate temperature and [CO2] thresholds leading to yield loss or yield gain, without re-running the original complex crop models. Our approach is illustrated with three yield datasets simulatedby 19 maize models, 26 wheat models, and 13 rice models. Several statistical models are fitted to thesedatasets, and are then used to analyze the variability of the yield response to [CO2] and temperature.Based on our results, we show that, for wheat, a [CO2] increase is likely to outweigh the negative effectof a temperature increase of +2◦C in... Presentar Todo |
Palabras claves : |
Climate change; CROP MODEL; Emulator; MAIZE; Meta-model; MODELIZACIÓN DE LOS CULTIVOS; RICE; Statistical model; WHEAT; Yield. |
Thesagro : |
ARROZ; CAMBIO CLIMÁTICO; MAÍZ; MODELOS ESTADISTICOS; TRIGO. |
Asunto categoría : |
A50 Investigación agraria |
Marc : |
LEADER 05363naa a2201417 a 4500 001 1053856 005 2019-10-09 008 2015 bl uuuu u00u1 u #d 022 $a0168-1923 024 7 $a10.1016/j.agrformet.2015.09.013$2DOI 100 1 $aMARCAIDA, M. 245 $aA statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration. 260 $c2015 500 $aArticle history: Received 6 March 2015 / Received in revised form 29 July 2015 / Accepted 20 September 2015 / Available online 1 October 2015. 520 $aABSTRACT. Ensembles of process-based crop models are increasingly used to simulate crop growth for scenariosof temperature and/or precipitation changes corresponding to different projections of atmospheric CO2concentrations. This approach generates large datasets with thousands of simulated crop yield data. Suchdatasets potentially provide new information but it is difficult to summarize them in a useful way due totheir structural complexities. An associated issue is that it is not straightforward to compare crops and tointerpolate the results to alternative climate scenarios not initially included in the simulation protocols.Here we demonstrate that statistical models based on random-coefficient regressions are able to emulateensembles of process-based crop models. An important advantage of the proposed statistical models isthat they can interpolate between temperature levels and between CO2concentration levels, and canthus be used to calculate temperature and [CO2] thresholds leading to yield loss or yield gain, without re-running the original complex crop models. Our approach is illustrated with three yield datasets simulatedby 19 maize models, 26 wheat models, and 13 rice models. Several statistical models are fitted to thesedatasets, and are then used to analyze the variability of the yield response to [CO2] and temperature.Based on our results, we show that, for wheat, a [CO2] increase is likely to outweigh the negative effectof a temperature increase of +2◦C in the considered sites. Compared to wheat, required levels of [CO2]increase are much higher for maize, and intermediate for rice. For all crops, uncertainties in simulatingclimate change impacts increase more with temperature than with elevated [CO2]. © 2015 Elsevier B.V. All rights reserved. 650 $aARROZ 650 $aCAMBIO CLIMÁTICO 650 $aMAÍZ 650 $aMODELOS ESTADISTICOS 650 $aTRIGO 653 $aClimate change 653 $aCROP MODEL 653 $aEmulator 653 $aMAIZE 653 $aMeta-model 653 $aMODELIZACIÓN DE LOS CULTIVOS 653 $aRICE 653 $aStatistical model 653 $aWHEAT 653 $aYield 700 1 $aASSENG, S. 700 1 $aEWERT, F. 700 1 $aBASSU, S. 700 1 $aDURAND, J.L. 700 1 $aLI, T. 700 1 $aMARTRE, P. 700 1 $aADAM, M. 700 1 $aAGGARWAL, P.K. 700 1 $aANGULO, C. 700 1 $aBARON, C. 700 1 $aBASSO, B. 700 1 $aBERTUZZI, P. 700 1 $aBIERNATH, C. 700 1 $aBOOGAARD, H. 700 1 $aBOOTE, K.J. 700 1 $aBOUMAN, B. 700 1 $aBREGAGLIO, S. 700 1 $aBRISSON, N. 700 1 $aBUIS, S. 700 1 $aCAMMARANO, D. 700 1 $aCHALLINOR, A.J. 700 1 $aCONFALONIERI, R. 700 1 $aCONIJN, J.G. 700 1 $aCORBEELS, M. 700 1 $aDERYNG, D. 700 1 $aDE SANCTIS, G. 700 1 $aDOLTRA, J. 700 1 $aFUMOTO, T. 700 1 $aGAYDON, D. 700 1 $aGAYLER, S. 700 1 $aGOLDBERG, R. 700 1 $aGRANT, R.F. 700 1 $aGRASSINI, P. 700 1 $aHATFIELD, J.L. 700 1 $aHASEGAWA, T. 700 1 $aHENG, L. 700 1 $aHOEK, S. 700 1 $aHOOKER, J. 700 1 $aHUNT, L.A. 700 1 $aINGWERSEN, J. 700 1 $aIZAURRALDE, R.C. 700 1 $aJONGSCHAAP, R.E.E. 700 1 $aJONES, J.W. 700 1 $aKEMANIAN, R.A. 700 1 $aKERSEBAUM, K.C. 700 1 $aKIM, S.-H. 700 1 $aLIZASO, J. 700 1 $aMÜLLER, C. 700 1 $aNAKAGAWA, H. 700 1 $aNARESH KUMAR, S. 700 1 $aNENDEL, C. 700 1 $aO'LEARY, G.J. 700 1 $aOLESEN, J.E. 700 1 $aORIOL, P. 700 1 $aOSBORNE, T.M. 700 1 $aPALOSUO, T. 700 1 $aPRAVIA, V. 700 1 $aPRIESACK, E. 700 1 $aRIPOCHE, D. 700 1 $aROSENZWEIG, C. 700 1 $aRUANE, A.C. 700 1 $aRUGET, F. 700 1 $aSAU, F. 700 1 $aSEMENOV, M.A. 700 1 $aSHCHERBAK, I. 700 1 $aSINGH, B. 700 1 $aSINGH, U. 700 1 $aSOO, H.K. 700 1 $aSTEDUTO, P. 700 1 $aSTÖCKLE, C. 700 1 $aSTRATONOVITCH, P. 700 1 $aSTRECK, T. 700 1 $aSUPIT, I. 700 1 $aTANG, L. 700 1 $aTAO, F. 700 1 $aTEIXEIRA, E.I. 700 1 $aTHORBURN, P. 700 1 $aTIMLIN, D. 700 1 $aTRAVASSO, M. 700 1 $aRÖTTER, R.P. 700 1 $aWAHA, K. 700 1 $aWALLACH, D. 700 1 $aWHITE, J.W. 700 1 $aWILKENS, P. 700 1 $aWILLIAMS, J.R. 700 1 $aWOLF, J. 700 1 $aYIN, X. 700 1 $aYOSHIDA, H. 700 1 $aZHANG, Z. 700 1 $aZHU, Y. 773 $tAgricultural and Forest Meteorology, 2015$gv.214-215, p. 483-493.
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INIA Las Brujas (LB) |
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Biblioteca (s) : |
INIA Tacuarembó. |
Fecha actual : |
27/11/2019 |
Actualizado : |
16/01/2020 |
Tipo de producción científica : |
Abstracts/Resúmenes |
Autor : |
REYNO, R.; DALLA RIZZA, M.; CASTILLO, A.; DO CANTO, J.; CONDON, F.; MENESES, L.; LATTANZI, F.; MONZA, J. |
Afiliación : |
RAFAEL ALEJANDRO REYNO PODESTA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARCO DALLA RIZZA VILARO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ALICIA MARIA CASTILLO SALLE, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JAVIER DO CANTO FAGUNDEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FEDERICO CONDON PRIANO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; LUCÍA VALERIA MENESES MEDINA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FERNANDO A. LATTANZI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; Universidad de la República (UdelaR)/ Facultad de Agronomía. |
Título : |
Forage breeding strategies in Uruguay: facing new challenges. [Resumen] |
Fecha de publicación : |
2019 |
Fuente / Imprenta : |
In: REDBIO; INIA (Instituto Nacional de Investigación Agropecuaria); REDBIO Argentina. X Encuentro Latinoamericano y del Caribe de Biotecnología Agropecuaria y XI Simposio Redbio Argentina. Libro de Resúmenes. Montevideo 12 - 15 Noviembre 2019. Montevideo (UY): INIA, 2019. p. 220. |
Serie : |
(INIA Serie Técnica; 253) |
ISBN : |
e-ISBN 978-9974-38-437-8 |
ISSN : |
1688-9266 |
DOI : |
http://doi.org/10.35676/INIA/ST.253 |
Idioma : |
Inglés |
Contenido : |
Productivity and persistence of sown pastures remain the main demands of Uruguayans producers, immersed in a context of sustainable intensification of production systems, with adaptation to climate change. In INIA Uruguay we have developed a wide range of approaches to address these issues. The exploration of the productive potential of native species and the incorporation of vegetative structures that favor competition and persistence as rhizomes are examples of the works that have been carried out in such diverse species as Paspalum notatum, Bromus auleticus, Lotus corniculatus, and Tall Fescue. With the addition of some biotechnological tools, we have also been planned long-term research and interspecific hybridization, seeking to incorporate new and higher productivity vegetative structures into agricultural interest species. An additional venue is to investigate and to develop those microorganisms responsible for biological nitrogen fixation in legumes, and for alkaloids production for plant protection as fungal endophytes in grasses. In the case of the rhizobia, a novel strategy was developed to seek and to characterize new strains better adapted to our
environmental conditions. The same strategy is now being used for developing new alfalfa strains. Fungal endophytes (from the Epichloë genus) present in a Bromus auleticus germplasm collection are being descripted and characterized for the first time. This
presentation resumes different strategies of genetic improvement of forage plants using contrasting cases. First, the case of native species Paspalum notatum and Bromus auleticus where the breeding scheme transited collection, molecular and agronomic characterization, and selection of genotypes adapted. Secondly, interspecific hybridization between species with the aim of combining vegetative structure with reproductive strategies, and finally investigating and developing different microorganism related to the productivity and persistence of forage species. MenosProductivity and persistence of sown pastures remain the main demands of Uruguayans producers, immersed in a context of sustainable intensification of production systems, with adaptation to climate change. In INIA Uruguay we have developed a wide range of approaches to address these issues. The exploration of the productive potential of native species and the incorporation of vegetative structures that favor competition and persistence as rhizomes are examples of the works that have been carried out in such diverse species as Paspalum notatum, Bromus auleticus, Lotus corniculatus, and Tall Fescue. With the addition of some biotechnological tools, we have also been planned long-term research and interspecific hybridization, seeking to incorporate new and higher productivity vegetative structures into agricultural interest species. An additional venue is to investigate and to develop those microorganisms responsible for biological nitrogen fixation in legumes, and for alkaloids production for plant protection as fungal endophytes in grasses. In the case of the rhizobia, a novel strategy was developed to seek and to characterize new strains better adapted to our
environmental conditions. The same strategy is now being used for developing new alfalfa strains. Fungal endophytes (from the Epichloë genus) present in a Bromus auleticus germplasm collection are being descripted and characterized for the first time. This
presentation resumes different strategies of genetic improvement... Presentar Todo |
Palabras claves : |
PASTURE. |
Asunto categoría : |
A50 Investigación agraria |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/14003/1/st-253-2019p220.pdf
|
Marc : |
LEADER 02909nam a2200241 a 4500 001 1060465 005 2020-01-16 008 2019 bl uuuu u01u1 u #d 022 $a1688-9266 024 7 $ahttp://doi.org/10.35676/INIA/ST.253$2DOI 100 1 $aREYNO, R. 245 $aForage breeding strategies in Uruguay$bfacing new challenges. [Resumen] 260 $aIn: REDBIO; INIA (Instituto Nacional de Investigación Agropecuaria); REDBIO Argentina. X Encuentro Latinoamericano y del Caribe de Biotecnología Agropecuaria y XI Simposio Redbio Argentina. Libro de Resúmenes. Montevideo 12 - 15 Noviembre 2019. Montevideo (UY): INIA, 2019. p. 220.$c2019 490 $a(INIA Serie Técnica; 253) 520 $aProductivity and persistence of sown pastures remain the main demands of Uruguayans producers, immersed in a context of sustainable intensification of production systems, with adaptation to climate change. In INIA Uruguay we have developed a wide range of approaches to address these issues. The exploration of the productive potential of native species and the incorporation of vegetative structures that favor competition and persistence as rhizomes are examples of the works that have been carried out in such diverse species as Paspalum notatum, Bromus auleticus, Lotus corniculatus, and Tall Fescue. With the addition of some biotechnological tools, we have also been planned long-term research and interspecific hybridization, seeking to incorporate new and higher productivity vegetative structures into agricultural interest species. An additional venue is to investigate and to develop those microorganisms responsible for biological nitrogen fixation in legumes, and for alkaloids production for plant protection as fungal endophytes in grasses. In the case of the rhizobia, a novel strategy was developed to seek and to characterize new strains better adapted to our environmental conditions. The same strategy is now being used for developing new alfalfa strains. Fungal endophytes (from the Epichloë genus) present in a Bromus auleticus germplasm collection are being descripted and characterized for the first time. This presentation resumes different strategies of genetic improvement of forage plants using contrasting cases. First, the case of native species Paspalum notatum and Bromus auleticus where the breeding scheme transited collection, molecular and agronomic characterization, and selection of genotypes adapted. Secondly, interspecific hybridization between species with the aim of combining vegetative structure with reproductive strategies, and finally investigating and developing different microorganism related to the productivity and persistence of forage species. 653 $aPASTURE 700 1 $aDALLA RIZZA, M. 700 1 $aCASTILLO, A. 700 1 $aDO CANTO, J. 700 1 $aCONDON, F. 700 1 $aMENESES, L. 700 1 $aLATTANZI, F. 700 1 $aMONZA, J.
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