Predicting maize phenology: intercomparison of functions for developmental response to temperature
- Autores
- Kumudini, S.; Andrade, Fernando Hector; Boote, K.J.; Brown, G.A.; Dzotsi, K.A.; Edmeades, G.O.; Gocken, T.; Goodwin, M.; Halter, A.L.; Hammer, G.L.; Hatfield, J.L.; Jones, J.W.; Kemanian, A.R.; Kim, Sung Hyun; Kiniry, J.; Lizaso, J.I.; Nendel, C.; Nielsen, R.L.; Parent, B.; Stӧckle, C.O.; Tardieu, F.; Thomison, P.R.; Timlin, D.J.; Vyn, T.J.; Wallach, D.; Yang, H.S.; Tollenaar, Matthijs
- Año de publicación
- 2014
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Accurate prediction of phenological development in maize (Zea mays L.) is fundamental to determining crop adaptation and yield potential. A number of thermal functions are used in crop models, but their relative precision in predicting maize development has not been quantified. The objectives of this study were (i) to evaluate the precision of eight thermal functions, (ii) to assess the effects of source data on the ability to differentiate among thermal functions, and (iii) to attribute the precision of thermal functions to their response across various temperature ranges. Data sets used in this study represent >1000 distinct maize hybrids, >50 geographic locations, and multiple planting dates and years. Thermal functions and calendar days were evaluated and grouped based on their temperature response and derivation as empirical linear, empirical nonlinear, and process-based functions. Precision in predicting phase durations from planting to anthesis or silking and from silking to physiological maturity was evaluated. Large data sets enabled increased differentiation of thermal functions, even when smaller data sets contained orthogonal, multi-location and -year data. At the highest level of differentiation, precision of thermal functions was in the order calendar days < empirical linear < process based < empirical nonlinear. Precision was associated with relatively low temperature sensitivity across the 10 to 26°C range. In contrast to other thermal functions, process-based functions were derived using supra-optimal temperatures, and consequently, they may better represent the developmental response of maize to supra-optimal temperatures. Supra-optimal temperatures could be more prevalent under future climate-change scenarios, but data sets in this study contained few data in that range.
EEA Balcarce
Fil: Kumudini, S. The Climate Corp; Estados Unidos
Fil: Andrade, Fernando Hector. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce-Unidad Integrada-Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina
Fil: Boote, K.J. University of Florida. Department of Agronomy; Estados Unidos
Fil: Brown, G.A. Breaking Ground; Estados Unidos
Fil: Dzotsi, K.A. University of Florida. Department of Agricultural and Biological Engineering; Estados Unidos
Fil: Edmeades, G.O. Hemmans; Nueva Zelanda
Fil: Gocken, T. Monsanto; Estados Unidos
Fil: Goodwin, M. Monsanto; Estados Unidos
Fil: Halter, A.L. Dupont-Pioneer; Estados Unidos
Fil: Hammer, G.L. University of Queensland; Australia
Fil: Hatfield, J.L. USDA-ARS. National Laboratory for Agriculture and the Environment; Estados Unidos
Fil: Jones, J.W. University of Florida. Department of Agricultural and Biological Engineering; Estados Unidos
Fil: Kemanian, A.R. Pennsylvania State University. Department of Plant Science; Estados Unidos
Fil: Kim, Sung Hyun. University of Washington. College of the Environment. School of Environmental and Forest Sciences; Estados Unidos
Fil: Kiniry, J. United States Department of Agriculture. ARS; Estados Unidos
Fil: Lizaso, J.I. Universidad Politécnica de Madrid. Departamento de Producción Vegetal; España
Fil: Nendel, C. Leibniz Centre for Agricultural Landscape Research. Institute of Landscape Systems Analysis; Alemania
Fil: Nielsen, R.L. Purdue University. Department of Agronomy; Estados Unidos
Fil: Parent, B. INRA. Laboratory d’Ecophysiologie des Plantes sous Stress Environnementaux; Francia
Fil: Stӧckle, C.O. Washington State University. Biological Systems Engineering; Estados Unidos
Fil: Tardieu, F. INRA. Laboratory d’Ecophysiologie des Plantes sous Stress Environnementaux; Francia
Fil: Thomison, P.R. Ohio State University. Department of Horticulture and Crop Science; Estados Unidos
Fil: Timlin, D.J. USDA-ARS. Crop Systems and Global Change Lab; Estados Unidos
Fil: Vyn, T.J. Purdue University. Department of Agronomy; Estados Unidos
Fil: Wallach, D. INRA. Agrosystèmes et développement territorial; Francia
Fil: Yang, H.S. Universidad de Nebraska - Lincoln. Department of Agronomy and Horticulture; Estados Unidos
Fil: Tollenaar, M. The Climate Corp; Estados Unidos - Fuente
- Agronomy Journal 106 (6) : 2087-2097 (2014)
- Materia
-
Maíz
Fenología
Temperatura
Etapas de Desarrollo de la Planta
Rendimiento
Maize
Phenology
Temperature
Plant Developmental Stages
Yields - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
.jpg)
- Institución
- Instituto Nacional de Tecnología Agropecuaria
- OAI Identificador
- oai:localhost:20.500.12123/5475
Ver los metadatos del registro completo
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Predicting maize phenology: intercomparison of functions for developmental response to temperatureKumudini, S.Andrade, Fernando HectorBoote, K.J.Brown, G.A.Dzotsi, K.A.Edmeades, G.O.Gocken, T.Goodwin, M.Halter, A.L.Hammer, G.L.Hatfield, J.L.Jones, J.W.Kemanian, A.R.Kim, Sung HyunKiniry, J.Lizaso, J.I.Nendel, C.Nielsen, R.L.Parent, B.Stӧckle, C.O.Tardieu, F.Thomison, P.R.Timlin, D.J.Vyn, T.J.Wallach, D.Yang, H.S.Tollenaar, MatthijsMaízFenologíaTemperaturaEtapas de Desarrollo de la PlantaRendimientoMaizePhenologyTemperaturePlant Developmental StagesYieldsAccurate prediction of phenological development in maize (Zea mays L.) is fundamental to determining crop adaptation and yield potential. A number of thermal functions are used in crop models, but their relative precision in predicting maize development has not been quantified. The objectives of this study were (i) to evaluate the precision of eight thermal functions, (ii) to assess the effects of source data on the ability to differentiate among thermal functions, and (iii) to attribute the precision of thermal functions to their response across various temperature ranges. Data sets used in this study represent >1000 distinct maize hybrids, >50 geographic locations, and multiple planting dates and years. Thermal functions and calendar days were evaluated and grouped based on their temperature response and derivation as empirical linear, empirical nonlinear, and process-based functions. Precision in predicting phase durations from planting to anthesis or silking and from silking to physiological maturity was evaluated. Large data sets enabled increased differentiation of thermal functions, even when smaller data sets contained orthogonal, multi-location and -year data. At the highest level of differentiation, precision of thermal functions was in the order calendar days < empirical linear < process based < empirical nonlinear. Precision was associated with relatively low temperature sensitivity across the 10 to 26°C range. In contrast to other thermal functions, process-based functions were derived using supra-optimal temperatures, and consequently, they may better represent the developmental response of maize to supra-optimal temperatures. Supra-optimal temperatures could be more prevalent under future climate-change scenarios, but data sets in this study contained few data in that range.EEA BalcarceFil: Kumudini, S. The Climate Corp; Estados UnidosFil: Andrade, Fernando Hector. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce-Unidad Integrada-Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; ArgentinaFil: Boote, K.J. University of Florida. Department of Agronomy; Estados UnidosFil: Brown, G.A. Breaking Ground; Estados UnidosFil: Dzotsi, K.A. University of Florida. Department of Agricultural and Biological Engineering; Estados UnidosFil: Edmeades, G.O. Hemmans; Nueva ZelandaFil: Gocken, T. Monsanto; Estados UnidosFil: Goodwin, M. Monsanto; Estados UnidosFil: Halter, A.L. Dupont-Pioneer; Estados UnidosFil: Hammer, G.L. University of Queensland; AustraliaFil: Hatfield, J.L. USDA-ARS. National Laboratory for Agriculture and the Environment; Estados UnidosFil: Jones, J.W. University of Florida. Department of Agricultural and Biological Engineering; Estados UnidosFil: Kemanian, A.R. Pennsylvania State University. Department of Plant Science; Estados UnidosFil: Kim, Sung Hyun. University of Washington. College of the Environment. School of Environmental and Forest Sciences; Estados UnidosFil: Kiniry, J. United States Department of Agriculture. ARS; Estados UnidosFil: Lizaso, J.I. Universidad Politécnica de Madrid. Departamento de Producción Vegetal; EspañaFil: Nendel, C. Leibniz Centre for Agricultural Landscape Research. Institute of Landscape Systems Analysis; AlemaniaFil: Nielsen, R.L. Purdue University. Department of Agronomy; Estados UnidosFil: Parent, B. INRA. Laboratory d’Ecophysiologie des Plantes sous Stress Environnementaux; FranciaFil: Stӧckle, C.O. Washington State University. Biological Systems Engineering; Estados UnidosFil: Tardieu, F. INRA. Laboratory d’Ecophysiologie des Plantes sous Stress Environnementaux; FranciaFil: Thomison, P.R. Ohio State University. Department of Horticulture and Crop Science; Estados UnidosFil: Timlin, D.J. USDA-ARS. Crop Systems and Global Change Lab; Estados UnidosFil: Vyn, T.J. Purdue University. Department of Agronomy; Estados UnidosFil: Wallach, D. INRA. Agrosystèmes et développement territorial; FranciaFil: Yang, H.S. Universidad de Nebraska - Lincoln. Department of Agronomy and Horticulture; Estados UnidosFil: Tollenaar, M. The Climate Corp; Estados UnidosAmerican Society of Agronomy2019-07-11T13:02:04Z2019-07-11T13:02:04Z2014-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://dl.sciencesocieties.org/publications/aj/abstracts/106/6/2087http://hdl.handle.net/20.500.12123/54750002-19621435-0645https://doi.org/10.2134/agronj14.0200Agronomy Journal 106 (6) : 2087-2097 (2014)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2025-10-23T11:17:00Zoai:localhost:20.500.12123/5475instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-10-23 11:17:00.659INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse |
| dc.title.none.fl_str_mv |
Predicting maize phenology: intercomparison of functions for developmental response to temperature |
| title |
Predicting maize phenology: intercomparison of functions for developmental response to temperature |
| spellingShingle |
Predicting maize phenology: intercomparison of functions for developmental response to temperature Kumudini, S. Maíz Fenología Temperatura Etapas de Desarrollo de la Planta Rendimiento Maize Phenology Temperature Plant Developmental Stages Yields |
| title_short |
Predicting maize phenology: intercomparison of functions for developmental response to temperature |
| title_full |
Predicting maize phenology: intercomparison of functions for developmental response to temperature |
| title_fullStr |
Predicting maize phenology: intercomparison of functions for developmental response to temperature |
| title_full_unstemmed |
Predicting maize phenology: intercomparison of functions for developmental response to temperature |
| title_sort |
Predicting maize phenology: intercomparison of functions for developmental response to temperature |
| dc.creator.none.fl_str_mv |
Kumudini, S. Andrade, Fernando Hector Boote, K.J. Brown, G.A. Dzotsi, K.A. Edmeades, G.O. Gocken, T. Goodwin, M. Halter, A.L. Hammer, G.L. Hatfield, J.L. Jones, J.W. Kemanian, A.R. Kim, Sung Hyun Kiniry, J. Lizaso, J.I. Nendel, C. Nielsen, R.L. Parent, B. Stӧckle, C.O. Tardieu, F. Thomison, P.R. Timlin, D.J. Vyn, T.J. Wallach, D. Yang, H.S. Tollenaar, Matthijs |
| author |
Kumudini, S. |
| author_facet |
Kumudini, S. Andrade, Fernando Hector Boote, K.J. Brown, G.A. Dzotsi, K.A. Edmeades, G.O. Gocken, T. Goodwin, M. Halter, A.L. Hammer, G.L. Hatfield, J.L. Jones, J.W. Kemanian, A.R. Kim, Sung Hyun Kiniry, J. Lizaso, J.I. Nendel, C. Nielsen, R.L. Parent, B. Stӧckle, C.O. Tardieu, F. Thomison, P.R. Timlin, D.J. Vyn, T.J. Wallach, D. Yang, H.S. Tollenaar, Matthijs |
| author_role |
author |
| author2 |
Andrade, Fernando Hector Boote, K.J. Brown, G.A. Dzotsi, K.A. Edmeades, G.O. Gocken, T. Goodwin, M. Halter, A.L. Hammer, G.L. Hatfield, J.L. Jones, J.W. Kemanian, A.R. Kim, Sung Hyun Kiniry, J. Lizaso, J.I. Nendel, C. Nielsen, R.L. Parent, B. Stӧckle, C.O. Tardieu, F. Thomison, P.R. Timlin, D.J. Vyn, T.J. Wallach, D. Yang, H.S. Tollenaar, Matthijs |
| author2_role |
author author author author author author author author author author author author author author author author author author author author author author author author author author |
| dc.subject.none.fl_str_mv |
Maíz Fenología Temperatura Etapas de Desarrollo de la Planta Rendimiento Maize Phenology Temperature Plant Developmental Stages Yields |
| topic |
Maíz Fenología Temperatura Etapas de Desarrollo de la Planta Rendimiento Maize Phenology Temperature Plant Developmental Stages Yields |
| dc.description.none.fl_txt_mv |
Accurate prediction of phenological development in maize (Zea mays L.) is fundamental to determining crop adaptation and yield potential. A number of thermal functions are used in crop models, but their relative precision in predicting maize development has not been quantified. The objectives of this study were (i) to evaluate the precision of eight thermal functions, (ii) to assess the effects of source data on the ability to differentiate among thermal functions, and (iii) to attribute the precision of thermal functions to their response across various temperature ranges. Data sets used in this study represent >1000 distinct maize hybrids, >50 geographic locations, and multiple planting dates and years. Thermal functions and calendar days were evaluated and grouped based on their temperature response and derivation as empirical linear, empirical nonlinear, and process-based functions. Precision in predicting phase durations from planting to anthesis or silking and from silking to physiological maturity was evaluated. Large data sets enabled increased differentiation of thermal functions, even when smaller data sets contained orthogonal, multi-location and -year data. At the highest level of differentiation, precision of thermal functions was in the order calendar days < empirical linear < process based < empirical nonlinear. Precision was associated with relatively low temperature sensitivity across the 10 to 26°C range. In contrast to other thermal functions, process-based functions were derived using supra-optimal temperatures, and consequently, they may better represent the developmental response of maize to supra-optimal temperatures. Supra-optimal temperatures could be more prevalent under future climate-change scenarios, but data sets in this study contained few data in that range. EEA Balcarce Fil: Kumudini, S. The Climate Corp; Estados Unidos Fil: Andrade, Fernando Hector. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce-Unidad Integrada-Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina Fil: Boote, K.J. University of Florida. Department of Agronomy; Estados Unidos Fil: Brown, G.A. Breaking Ground; Estados Unidos Fil: Dzotsi, K.A. University of Florida. Department of Agricultural and Biological Engineering; Estados Unidos Fil: Edmeades, G.O. Hemmans; Nueva Zelanda Fil: Gocken, T. Monsanto; Estados Unidos Fil: Goodwin, M. Monsanto; Estados Unidos Fil: Halter, A.L. Dupont-Pioneer; Estados Unidos Fil: Hammer, G.L. University of Queensland; Australia Fil: Hatfield, J.L. USDA-ARS. National Laboratory for Agriculture and the Environment; Estados Unidos Fil: Jones, J.W. University of Florida. Department of Agricultural and Biological Engineering; Estados Unidos Fil: Kemanian, A.R. Pennsylvania State University. Department of Plant Science; Estados Unidos Fil: Kim, Sung Hyun. University of Washington. College of the Environment. School of Environmental and Forest Sciences; Estados Unidos Fil: Kiniry, J. United States Department of Agriculture. ARS; Estados Unidos Fil: Lizaso, J.I. Universidad Politécnica de Madrid. Departamento de Producción Vegetal; España Fil: Nendel, C. Leibniz Centre for Agricultural Landscape Research. Institute of Landscape Systems Analysis; Alemania Fil: Nielsen, R.L. Purdue University. Department of Agronomy; Estados Unidos Fil: Parent, B. INRA. Laboratory d’Ecophysiologie des Plantes sous Stress Environnementaux; Francia Fil: Stӧckle, C.O. Washington State University. Biological Systems Engineering; Estados Unidos Fil: Tardieu, F. INRA. Laboratory d’Ecophysiologie des Plantes sous Stress Environnementaux; Francia Fil: Thomison, P.R. Ohio State University. Department of Horticulture and Crop Science; Estados Unidos Fil: Timlin, D.J. USDA-ARS. Crop Systems and Global Change Lab; Estados Unidos Fil: Vyn, T.J. Purdue University. Department of Agronomy; Estados Unidos Fil: Wallach, D. INRA. Agrosystèmes et développement territorial; Francia Fil: Yang, H.S. Universidad de Nebraska - Lincoln. Department of Agronomy and Horticulture; Estados Unidos Fil: Tollenaar, M. The Climate Corp; Estados Unidos |
| description |
Accurate prediction of phenological development in maize (Zea mays L.) is fundamental to determining crop adaptation and yield potential. A number of thermal functions are used in crop models, but their relative precision in predicting maize development has not been quantified. The objectives of this study were (i) to evaluate the precision of eight thermal functions, (ii) to assess the effects of source data on the ability to differentiate among thermal functions, and (iii) to attribute the precision of thermal functions to their response across various temperature ranges. Data sets used in this study represent >1000 distinct maize hybrids, >50 geographic locations, and multiple planting dates and years. Thermal functions and calendar days were evaluated and grouped based on their temperature response and derivation as empirical linear, empirical nonlinear, and process-based functions. Precision in predicting phase durations from planting to anthesis or silking and from silking to physiological maturity was evaluated. Large data sets enabled increased differentiation of thermal functions, even when smaller data sets contained orthogonal, multi-location and -year data. At the highest level of differentiation, precision of thermal functions was in the order calendar days < empirical linear < process based < empirical nonlinear. Precision was associated with relatively low temperature sensitivity across the 10 to 26°C range. In contrast to other thermal functions, process-based functions were derived using supra-optimal temperatures, and consequently, they may better represent the developmental response of maize to supra-optimal temperatures. Supra-optimal temperatures could be more prevalent under future climate-change scenarios, but data sets in this study contained few data in that range. |
| publishDate |
2014 |
| dc.date.none.fl_str_mv |
2014-12 2019-07-11T13:02:04Z 2019-07-11T13:02:04Z |
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info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
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article |
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publishedVersion |
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https://dl.sciencesocieties.org/publications/aj/abstracts/106/6/2087 http://hdl.handle.net/20.500.12123/5475 0002-1962 1435-0645 https://doi.org/10.2134/agronj14.0200 |
| url |
https://dl.sciencesocieties.org/publications/aj/abstracts/106/6/2087 http://hdl.handle.net/20.500.12123/5475 https://doi.org/10.2134/agronj14.0200 |
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0002-1962 1435-0645 |
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eng |
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eng |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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application/pdf |
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American Society of Agronomy |
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American Society of Agronomy |
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