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Registro completo
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Biblioteca (s) : |
INIA Treinta y Tres. |
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Fecha : |
15/06/2021 |
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Actualizado : |
04/04/2022 |
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Autor : |
MATSUO, T.; HOSHIKAWA, K.; KUMAZAWA, K.; ISHII, R.; ISHIHARA, K.; HIRATA, H. (Ed.). |
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Título : |
Science of the rice plant. |
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Fecha de publicación : |
1995 |
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Fuente / Imprenta : |
Tokyo (Japón): Japón. Ministry of Agriculture, Forestry and Fisheries, 1995. |
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Páginas : |
3v. |
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ISBN : |
4-540-93015-X |
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Idioma : |
Inglés |
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Notas : |
Se posee : v1 Morphology ; v2 Phisiology ; v3 Genetics." "supplementary Volume: indices" |
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Thesagro : |
ABSORCION DE SUSTANCIAS NUTRITIVAS; ACIDO GIBERELICO; ADAPTACION; ADN RECOMBINADORECURSOS GENETICOS; ALMACENAMIENTO; ALMACENAMIENTO DE SEMILLAS; ANATOMIA DE LA PLANTA; ARROZ; AUXINAS; CALCIO; CALIDAD; CELULAS; CITOQUININAS; CLASIFICACION; COMPOSICION QUIMICA; CRECIMIENTO; CULTIVO DE TEJIDOS; DAÑOS; DAÑOS POR EL VIENTO; DAÑOS POR LA HELADA; DISTRIBUCION GEOGRAFICA; DORMICION; ENFERMEDADES DE LAS PLANTAS; ENVEJECIMIENTO; ETAPAS DE DESARROLLO DE LA PLANTA; ETILENO; FACTORES AMBIENTALES; FIJACION DEL NITROGENO; FISIOLOGIA VEGETAL; FITOMEJORAMIENTO; FLORACION; FLORES; FOSFATOS; FOTOSINTESIS; FUSION DEL PROTOPLASTO; GENETICA; GERMINACION; GRANOS; HERENCIA GENETICA; HOJAS; INFLORESCENCIAS; INSECTOS DAÑINOS; MADURACION; MADUREZ; MAGNESIO; METABOLISMO DEL NITROGENO; MUTACION INDIVIDUAL; NECESIDADES DE AGUA; NECESIDADES DE LAS PLANTAS; OLIGOELEMENTOS; ORGANOS VEGETATIVOS DE LAS PLANTAS; ORYZA; PERDIDAS; PLAGAS DE PLANTAS; PLAGUICIDAS; PODER GERMINATIVO; POLUCION; POLUCION DEL AGUA; POLUCION DEL AIRE; POLUCION DEL SUELO; POTASIO; PROCEDENCIA; PRODUCTOS DE ORIGEN VEGETAL; PROPIEDADES FISICO-QUIMICAS; RAICES; RELACIONES PLANTA AGUA; RESISTENCIA A LA ENFERMEDAD; RESISTENCIA A LA SEQUIA; RESISTENCIA A LAS PLAGAS; RESPIRACION; SULFUROS; SUSTANCIAS DE CRECIMIENTO VEGETAL; TALLO; TAXONOMIA; TOXICIDAD; TRANSPIRACION; TRASTORNOS FUNCIONALES; VALOR NUTRITIVO; VARIEDADES; VIABILIDAD DE LA SEMILLA. |
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Asunto categoría : |
-- |
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Marc : |
LEADER 03185nam a2201153 a 4500
001 1062132
005 2022-04-04
008 1995 bl uuuu u00u1 u #d
020 $a4-540-93015-X
100 1 $aMATSUO, T.
245 $aScience of the rice plant.
260 $aTokyo (Japón): Japón. Ministry of Agriculture, Forestry and Fisheries$c1995
300 $a3v.
500 $aSe posee : v1 Morphology ; v2 Phisiology ; v3 Genetics." "supplementary Volume: indices"
650 $aABSORCION DE SUSTANCIAS NUTRITIVAS
650 $aACIDO GIBERELICO
650 $aADAPTACION
650 $aADN RECOMBINADORECURSOS GENETICOS
650 $aALMACENAMIENTO
650 $aALMACENAMIENTO DE SEMILLAS
650 $aANATOMIA DE LA PLANTA
650 $aARROZ
650 $aAUXINAS
650 $aCALCIO
650 $aCALIDAD
650 $aCELULAS
650 $aCITOQUININAS
650 $aCLASIFICACION
650 $aCOMPOSICION QUIMICA
650 $aCRECIMIENTO
650 $aCULTIVO DE TEJIDOS
650 $aDAÑOS
650 $aDAÑOS POR EL VIENTO
650 $aDAÑOS POR LA HELADA
650 $aDISTRIBUCION GEOGRAFICA
650 $aDORMICION
650 $aENFERMEDADES DE LAS PLANTAS
650 $aENVEJECIMIENTO
650 $aETAPAS DE DESARROLLO DE LA PLANTA
650 $aETILENO
650 $aFACTORES AMBIENTALES
650 $aFIJACION DEL NITROGENO
650 $aFISIOLOGIA VEGETAL
650 $aFITOMEJORAMIENTO
650 $aFLORACION
650 $aFLORES
650 $aFOSFATOS
650 $aFOTOSINTESIS
650 $aFUSION DEL PROTOPLASTO
650 $aGENETICA
650 $aGERMINACION
650 $aGRANOS
650 $aHERENCIA GENETICA
650 $aHOJAS
650 $aINFLORESCENCIAS
650 $aINSECTOS DAÑINOS
650 $aMADURACION
650 $aMADUREZ
650 $aMAGNESIO
650 $aMETABOLISMO DEL NITROGENO
650 $aMUTACION INDIVIDUAL
650 $aNECESIDADES DE AGUA
650 $aNECESIDADES DE LAS PLANTAS
650 $aOLIGOELEMENTOS
650 $aORGANOS VEGETATIVOS DE LAS PLANTAS
650 $aORYZA
650 $aPERDIDAS
650 $aPLAGAS DE PLANTAS
650 $aPLAGUICIDAS
650 $aPODER GERMINATIVO
650 $aPOLUCION
650 $aPOLUCION DEL AGUA
650 $aPOLUCION DEL AIRE
650 $aPOLUCION DEL SUELO
650 $aPOTASIO
650 $aPROCEDENCIA
650 $aPRODUCTOS DE ORIGEN VEGETAL
650 $aPROPIEDADES FISICO-QUIMICAS
650 $aRAICES
650 $aRELACIONES PLANTA AGUA
650 $aRESISTENCIA A LA ENFERMEDAD
650 $aRESISTENCIA A LA SEQUIA
650 $aRESISTENCIA A LAS PLAGAS
650 $aRESPIRACION
650 $aSULFUROS
650 $aSUSTANCIAS DE CRECIMIENTO VEGETAL
650 $aTALLO
650 $aTAXONOMIA
650 $aTOXICIDAD
650 $aTRANSPIRACION
650 $aTRASTORNOS FUNCIONALES
650 $aVALOR NUTRITIVO
650 $aVARIEDADES
650 $aVIABILIDAD DE LA SEMILLA
700 1 $aHOSHIKAWA, K.
700 1 $aKUMAZAWA, K.
700 1 $aISHII, R.
700 1 $aISHIHARA, K.
700 1 $aHIRATA, H.
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Registro original : |
INIA Treinta y Tres (TT) |
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 | Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas; INIA Treinta y Tres. |
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Fecha actual : |
12/11/2015 |
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Actualizado : |
09/10/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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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. |
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Afiliación : |
MARIA VIRGINIA PRAVIA NIN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration. |
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Fecha de publicación : |
2015 |
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Fuente / Imprenta : |
Agricultural and Forest Meteorology, 2015, v.214-215, p. 483-493. |
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ISSN : |
0168-1923 |
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DOI : |
10.1016/j.agrformet.2015.09.013 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 6 March 2015 / Received in revised form 29 July 2015 / Accepted 20 September 2015 / Available online 1 October 2015. |
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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 |
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Palabras claves : |
Climate change; CROP MODEL; Emulator; MAIZE; Meta-model; MODELIZACIÓN DE LOS CULTIVOS; RICE; Statistical model; WHEAT; Yield. |
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Thesagro : |
ARROZ; CAMBIO CLIMÁTICO; MAÍZ; MODELOS ESTADISTICOS; TRIGO. |
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Asunto categoría : |
A50 Investigación agraria |
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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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