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
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/38176

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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling 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 Técnicas2025-09-29T10:00:34Zoai: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:34982025-09-29 10:00:34.835CONICET 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
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 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
language eng
dc.relation.none.fl_str_mv 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
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Amer Soc Agronomy
publisher.none.fl_str_mv Amer Soc Agronomy
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
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repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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