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
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/5475

id INTADig_258cd956ed5aac8dd436cbc0475dc7f9
oai_identifier_str oai:localhost:20.500.12123/5475
network_acronym_str INTADig
repository_id_str l
network_name_str INTA Digital (INTA)
spelling 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)2025-09-29T13:44:43Zoai: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:l2025-09-29 13:44:43.365INTA 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
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv 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
identifier_str_mv 0002-1962
1435-0645
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv American Society of Agronomy
publisher.none.fl_str_mv American Society of Agronomy
dc.source.none.fl_str_mv Agronomy Journal 106 (6) : 2087-2097 (2014)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
_version_ 1844619135582994432
score 12.559606