Predicting maize phenology: Intercomparison of functions for developmental response to temperature
- Autores
- Kumudini , S.; Andrade, Fernando Héctor; 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, M.
- 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.
Fil: Kumudini , S.. The Climate Corp; Estados Unidos
Fil: Andrade, Fernando Héctor. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Balcarce. Area de Invest.en Agronomia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Mar del Plata; Argentina
Fil: Boote , K. J.. University of Florida; Estados Unidos
Fil: Brown , G. A.. Breaking Ground; Estados Unidos
Fil: Dzotsi, K. A.. University of Florida; 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.. Pennsylvania State University; Estados Unidos
Fil: Hatfield, J. L.. National Laboratory for Agriculture and the Environment; Estados Unidos
Fil: Jones, J. W.. University of Florida; Estados Unidos
Fil: Kemanian, A. R.. Pennsylvania State University; Estados Unidos
Fil: Kim, Sung Hyun. National Laboratory for Agriculture and the Environment; Estados Unidos
Fil: Kiniry, J.. Grassland Soil and Water Research Laboratory; Estados Unidos
Fil: Lizaso, J. I.. Universidad Politécnica de Madrid; España
Fil: Nendel, C.. Institute of Landscape Systems Analysis; Alemania
Fil: Nielsen, R. L.. Purdue University; Estados Unidos
Fil: Parent, B.. Laboratory d’Ecophysiologie des Plantes sous Stress Environnementaux; Francia
Fil: Stӧckle, C. O.. Washington State University; Estados Unidos
Fil: Tardieu, F.. Laboratory d’Ecophysiologie des Plantes sous Stress Environnementaux; Francia
Fil: Thomison, P. R.. Ohio State University; Estados Unidos
Fil: Timlin, D. J.. Crop Systems and Global Change Lab; Estados Unidos
Fil: Vyn, T. J.. Purdue University; Estados Unidos
Fil: Wallach, D.. Universidad de Nebraska - Lincoln; Estados Unidos
Fil: Yang, H. S.. Universidad de Nebraska - Lincoln; Estados Unidos
Fil: Tollenaar, M.. The Climate Corp; Estados Unidos - Materia
-
Maize
Phenology
Modelling - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
.jpg)
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/38176
Ver los metadatos del registro completo
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Predicting maize phenology: Intercomparison of functions for developmental response to temperatureKumudini , S.Andrade, Fernando HéctorBoote , 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, M.MaizePhenologyModellinghttps://purl.org/becyt/ford/4.1https://purl.org/becyt/ford/4Accurate 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.Fil: Kumudini , S.. The Climate Corp; Estados UnidosFil: Andrade, Fernando Héctor. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Balcarce. Area de Invest.en Agronomia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Mar del Plata; ArgentinaFil: Boote , K. J.. University of Florida; Estados UnidosFil: Brown , G. A.. Breaking Ground; Estados UnidosFil: Dzotsi, K. A.. University of Florida; 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.. Pennsylvania State University; Estados UnidosFil: Hatfield, J. L.. National Laboratory for Agriculture and the Environment; Estados UnidosFil: Jones, J. W.. University of Florida; Estados UnidosFil: Kemanian, A. R.. Pennsylvania State University; Estados UnidosFil: Kim, Sung Hyun. National Laboratory for Agriculture and the Environment; Estados UnidosFil: Kiniry, J.. Grassland Soil and Water Research Laboratory; Estados UnidosFil: Lizaso, J. I.. Universidad Politécnica de Madrid; EspañaFil: Nendel, C.. Institute of Landscape Systems Analysis; AlemaniaFil: Nielsen, R. L.. Purdue University; Estados UnidosFil: Parent, B.. Laboratory d’Ecophysiologie des Plantes sous Stress Environnementaux; FranciaFil: Stӧckle, C. O.. Washington State University; Estados UnidosFil: Tardieu, F.. Laboratory d’Ecophysiologie des Plantes sous Stress Environnementaux; FranciaFil: Thomison, P. R.. Ohio State University; Estados UnidosFil: Timlin, D. J.. Crop Systems and Global Change Lab; Estados UnidosFil: Vyn, T. J.. Purdue University; Estados UnidosFil: Wallach, D.. Universidad de Nebraska - Lincoln; Estados UnidosFil: Yang, H. S.. Universidad de Nebraska - Lincoln; Estados UnidosFil: Tollenaar, M.. The Climate Corp; Estados UnidosAmer Soc Agronomy2014-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/38176Kumudini , S.; Andrade, Fernando Héctor; Boote , K. J.; Brown , G. A.; Dzotsi, K. A.; et al.; Predicting maize phenology: Intercomparison of functions for developmental response to temperature; Amer Soc Agronomy; Agronomy Journal; 106; 6; 11-2014; 2087-20970002-1962CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.2134/agronj14.0200info:eu-repo/semantics/altIdentifier/url/https://dl.sciencesocieties.org/publications/aj/abstracts/106/6/2087info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:30:05Zoai:ri.conicet.gov.ar:11336/38176instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 11:30:05.216CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
| 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. Maize Phenology Modelling |
| 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 Héctor 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, M. |
| author |
Kumudini , S. |
| author_facet |
Kumudini , S. Andrade, Fernando Héctor 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, M. |
| author_role |
author |
| author2 |
Andrade, Fernando Héctor 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, M. |
| 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 |
Maize Phenology Modelling |
| topic |
Maize Phenology Modelling |
| purl_subject.fl_str_mv |
https://purl.org/becyt/ford/4.1 https://purl.org/becyt/ford/4 |
| 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. Fil: Kumudini , S.. The Climate Corp; Estados Unidos Fil: Andrade, Fernando Héctor. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Balcarce. Area de Invest.en Agronomia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Mar del Plata; Argentina Fil: Boote , K. J.. University of Florida; Estados Unidos Fil: Brown , G. A.. Breaking Ground; Estados Unidos Fil: Dzotsi, K. A.. University of Florida; 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.. Pennsylvania State University; Estados Unidos Fil: Hatfield, J. L.. National Laboratory for Agriculture and the Environment; Estados Unidos Fil: Jones, J. W.. University of Florida; Estados Unidos Fil: Kemanian, A. R.. Pennsylvania State University; Estados Unidos Fil: Kim, Sung Hyun. National Laboratory for Agriculture and the Environment; Estados Unidos Fil: Kiniry, J.. Grassland Soil and Water Research Laboratory; Estados Unidos Fil: Lizaso, J. I.. Universidad Politécnica de Madrid; España Fil: Nendel, C.. Institute of Landscape Systems Analysis; Alemania Fil: Nielsen, R. L.. Purdue University; Estados Unidos Fil: Parent, B.. Laboratory d’Ecophysiologie des Plantes sous Stress Environnementaux; Francia Fil: Stӧckle, C. O.. Washington State University; Estados Unidos Fil: Tardieu, F.. Laboratory d’Ecophysiologie des Plantes sous Stress Environnementaux; Francia Fil: Thomison, P. R.. Ohio State University; Estados Unidos Fil: Timlin, D. J.. Crop Systems and Global Change Lab; Estados Unidos Fil: Vyn, T. J.. Purdue University; Estados Unidos Fil: Wallach, D.. Universidad de Nebraska - Lincoln; Estados Unidos Fil: Yang, H. S.. Universidad de Nebraska - Lincoln; 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 |
2014-11 |
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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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http://hdl.handle.net/11336/38176 Kumudini , S.; Andrade, Fernando Héctor; Boote , K. J.; Brown , G. A.; Dzotsi, K. A.; et al.; Predicting maize phenology: Intercomparison of functions for developmental response to temperature; Amer Soc Agronomy; Agronomy Journal; 106; 6; 11-2014; 2087-2097 0002-1962 CONICET Digital CONICET |
| url |
http://hdl.handle.net/11336/38176 |
| identifier_str_mv |
Kumudini , S.; Andrade, Fernando Héctor; Boote , K. J.; Brown , G. A.; Dzotsi, K. A.; et al.; Predicting maize phenology: Intercomparison of functions for developmental response to temperature; Amer Soc Agronomy; Agronomy Journal; 106; 6; 11-2014; 2087-2097 0002-1962 CONICET Digital CONICET |
| dc.language.none.fl_str_mv |
eng |
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eng |
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info:eu-repo/semantics/altIdentifier/doi/10.2134/agronj14.0200 info:eu-repo/semantics/altIdentifier/url/https://dl.sciencesocieties.org/publications/aj/abstracts/106/6/2087 |
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openAccess |
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application/pdf application/pdf application/pdf |
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Amer Soc Agronomy |
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Amer Soc Agronomy |
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