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Predicting maize phenology : intercomparaison of functions for developmental response to temperature
- Source :
- Agronomy Journal 6 (106), 2087-2097. (2014), CONICET Digital (CONICET), Consejo Nacional de Investigaciones Científicas y Técnicas, instacron:CONICET, Agronomy Journal, Agronomy Journal, American Society of Agronomy, 2014, 106 (6), pp.2087-2097. ⟨10.2134/agronj14.0200⟩, Agronomy Journal 106 (6) : 2087-2097 (2014), INTA Digital (INTA), Instituto Nacional de Tecnología Agropecuaria, instacron:INTA
- Publication Year :
- 2014
-
Abstract
- 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
- Subjects :
- Plant Developmental Stages
Yields
Source data
[SDV]Life Sciences [q-bio]
Modelling
[SHS]Humanities and Social Sciences
Anthesis
Range (statistics)
Maíz
Etapas de Desarrollo de la Planta
Mathematics
2. Zero hunger
Rendimiento
maize phenology
Phenology
Agricultura
developmental response
Temperature
Sowing
Contrast (statistics)
temperature
Temperatura
Maize
Nonlinear system
Fenología
Agronomy
CIENCIAS AGRÍCOLAS
[SDE]Environmental Sciences
purl.org/becyt/ford/4.1 [https]
Agricultura, Silvicultura y Pesca
Agronomy and Crop Science
Temperature response
purl.org/becyt/ford/4 [https]
Subjects
Details
- Language :
- English
- ISSN :
- 00021962
- Database :
- OpenAIRE
- Journal :
- Agronomy Journal 6 (106), 2087-2097. (2014), CONICET Digital (CONICET), Consejo Nacional de Investigaciones Científicas y Técnicas, instacron:CONICET, Agronomy Journal, Agronomy Journal, American Society of Agronomy, 2014, 106 (6), pp.2087-2097. ⟨10.2134/agronj14.0200⟩, Agronomy Journal 106 (6) : 2087-2097 (2014), INTA Digital (INTA), Instituto Nacional de Tecnología Agropecuaria, instacron:INTA
- Accession number :
- edsair.doi.dedup.....2460193d7bec6c94c9d27c26f088e9c9