| |
|
|
|
Registro completo
|
|
Biblioteca (s) : |
INIA Las Brujas. |
|
Fecha : |
02/02/2022 |
|
Actualizado : |
02/02/2022 |
|
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
|
Autor : |
MILECH, C.G.; DINI, M.; FRANZONI, R.C.; RASEIRA, M.C.B. |
|
Afiliación : |
CHAIANE GOVEA MILECH, Universidade Federal de Pelotas, Programa de Pós-graduação em Agronomia (Fruticultura de Clima Temperado), Pelotas, Rio Grande do Sul, Brazil; MAXIMILIANO ANTONIO DINI VIÑOLY, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; RODRIGO CEZAR FRANZON, Embrapa Clima Temperado, Pelotas, Rio Grande do Sul, Brazil; MARIA DO CARMO BASSOLS RASEIRA, Embrapa Clima Temperado, Pelotas, Rio Grande do Sul, Brazil. |
|
Título : |
Chilling requirement of four peach cultivars estimated by changes in flower bud weights. * |
|
Fecha de publicación : |
2022 |
|
Fuente / Imprenta : |
Rev. Ceres, 2022, , v.69, n.1, p.22-30. OPEN ACCESS. https://doi.org/10.1590/0034-737X202269010004 |
|
ISSN : |
2177-3491 |
|
DOI : |
10.1590/0034-737X202269010004 |
|
Idioma : |
Inglés |
|
Notas : |
Article history: Received 15 Oct 2020; Accepted 06 June 2021; Published 14 Jan 2022; Date of issue Jan-Feb 2022.
*This work is part of the first author?s doctoral thesis.
Corresponding author:Maria do Carmo Bassols Raseira, mailto: maria.bassols@embrapa.br |
|
Contenido : |
ABSTRACT.- The adaptation of temperate fruit crops is a challenge being increased by the global warming. Chilling requirement is a key factor for adaptation. The objective of this study was to estimate the chilling requirement of peach cultivars BRS Bonão, Esmeralda, Granada and Eragil, using the Tabuenca test. Chilling accumulation was computed using four different chilling hour (? 7.2 ºC and ? 11 ºC) models; and chill units using the Low Chill model and the Taiwan model. The fresh bud weight and bud water contents were also evaluated. The Tabuenca test (based on differences in bud´s dry weight) showed a fairly good efficiency for estimating the end of dormancy in peach. However, under mild winter conditions, it is better to use fresh bud weights. Either one of three chilling accumulation computation models (temperature ? 7.2 °C, ? 11°C, or Taiwan model) is suitable to classify comparatively different cultivars, but none is accurate enough to conclude on the adaptation of a given cultivar to a specific site. Using hours of temperatures ? 11 ºC: ?BRS Bonão? needed around 180 hours for dormancy release; ?Esmeralda? around 250 hours; ?Granada? between 300 and 400 hours, and ?Eragil? more than 500 hours. |
|
Palabras claves : |
Dormancy; Low chill cultivars; Mild winter; Prunus persica (L.) Batsch;; Tabuenca test. |
|
Asunto categoría : |
F01 Cultivo |
|
URL : |
https://www.scielo.br/j/rceres/a/3zKkCKRMZrjwRC6hhMxRpvn/?format=pdf&lang=en
|
|
Marc : |
LEADER 02262naa a2200253 a 4500
001 1062731
005 2022-02-02
008 2022 bl uuuu u00u1 u #d
022 $a2177-3491
024 7 $a10.1590/0034-737X202269010004$2DOI
100 1 $aMILECH, C.G.
245 $aChilling requirement of four peach cultivars estimated by changes in flower bud weights. *$h[electronic resource]
260 $c2022
500 $aArticle history: Received 15 Oct 2020; Accepted 06 June 2021; Published 14 Jan 2022; Date of issue Jan-Feb 2022. *This work is part of the first author?s doctoral thesis. Corresponding author:Maria do Carmo Bassols Raseira, mailto: maria.bassols@embrapa.br
520 $aABSTRACT.- The adaptation of temperate fruit crops is a challenge being increased by the global warming. Chilling requirement is a key factor for adaptation. The objective of this study was to estimate the chilling requirement of peach cultivars BRS Bonão, Esmeralda, Granada and Eragil, using the Tabuenca test. Chilling accumulation was computed using four different chilling hour (? 7.2 ºC and ? 11 ºC) models; and chill units using the Low Chill model and the Taiwan model. The fresh bud weight and bud water contents were also evaluated. The Tabuenca test (based on differences in bud´s dry weight) showed a fairly good efficiency for estimating the end of dormancy in peach. However, under mild winter conditions, it is better to use fresh bud weights. Either one of three chilling accumulation computation models (temperature ? 7.2 °C, ? 11°C, or Taiwan model) is suitable to classify comparatively different cultivars, but none is accurate enough to conclude on the adaptation of a given cultivar to a specific site. Using hours of temperatures ? 11 ºC: ?BRS Bonão? needed around 180 hours for dormancy release; ?Esmeralda? around 250 hours; ?Granada? between 300 and 400 hours, and ?Eragil? more than 500 hours.
653 $aDormancy
653 $aLow chill cultivars
653 $aMild winter
653 $aPrunus persica (L.) Batsch;
653 $aTabuenca test
700 1 $aDINI, M.
700 1 $aFRANZONI, R.C.
700 1 $aRASEIRA, M.C.B.
773 $tRev. Ceres, 2022,$gv.69, n.1, p.22-30. OPEN ACCESS. https://doi.org/10.1590/0034-737X202269010004
Descargar
Esconder MarcPresentar Marc Completo |
|
Registro original : |
INIA Las Brujas (LB) |
|
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
|
|
 | Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
|
Registro completo
|
|
Biblioteca (s) : |
INIA Las Brujas; INIA Treinta y Tres. |
|
Fecha actual : |
12/11/2015 |
|
Actualizado : |
09/10/2019 |
|
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
|
Circulación / Nivel : |
Internacional - -- |
|
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.
Descargar
Esconder MarcPresentar Marc Completo |
|
Registro original : |
INIA Las Brujas (LB) |
|
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
| Expresión de búsqueda válido. Check! |
|
|
