Registro:
Título en inglés:
A high - yielding traits experiment for modeling potential production of wheat : field experiments and AgMIP - Wheat multi - model simulations
Autor/es:
Guarin, José Rafael; Martre, Pierre; Ewert, Frank; Webber, Heidi; Dueri, Sibylle; Calderini, Daniel Fernando; Reynolds, Matthew P.; Miralles, Daniel Julio; García, Guillermo Ariel
Filiación:
Guarin, José Rafael. University of Florida. Agricultural and Biological Engineering Department. Gainesville, FL, USA.
Guarin, Jose Rafael. Columbia University. Center for Climate Systems Research. New York, NY, USA.
Guarin, Jose Rafael. NASA Goddard Institute for Space Studies. New York, NY, USA.
Martre, Pierre. Laboratory for Plant Ecophysiology under Environmental Stress (LEPSE). INRAE - Univ Montpellier. Institut Agro Montpellier. Laboratoire d'Écophysiologie des Plantes sous Stress Environnementaux (LEPSE). Montpellier, France.
Ewert, Frank. University of Bonn. Institute of Crop Science and Resource Conservation INRES. Bonn, Germany.
Ewert, Frank. Leibniz Centre for Agricultural Landscape Research (ZALF). Müncheberg, Germany.
Webber, Heidi. University of Bonn. Institute of Crop Science and Resource Conservation INRES. Bonn, Germany.
Webber, Heidi. Leibniz Centre for Agricultural Landscape Research (ZALF). Müncheberg, Germany.
Dueri, Sibylle. Laboratory for Plant Ecophysiology under Environmental Stress (LEPSE). INRAE - Univ Montpellier. Institut Agro Montpellier. Laboratoire d'Écophysiologie des Plantes sous Stress Environnementaux (LEPSE). Montpellier, France.
Calderini, Daniel Fernando. Austral University of Chile. Institute of Plant Production and Protection. Valdivia, Chile.
Reynolds, Matthew P. Centro Internacional de Mejoramiento de Maíz y Trigo (CIMMYT). México DF, México.
Miralles, Daniel Julio. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura (IFEVA). Buenos Aires, Argentina.
Miralles, Daniel Julio. CONICET – Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura (IFEVA). Buenos Aires, Argentina.
Miralles, Daniel Julio. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Buenos Aires, Argentina.
García, Guillermo Ariel. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura (IFEVA). Buenos Aires, Argentina.
García, Guillermo Ariel. CONICET – Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura (IFEVA). Buenos Aires, Argentina.
García, Guillermo Ariel. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Buenos Aires, Argentina.
Título revista:
Open Data Journal for Agricultural Research
Temas:
WHEAT; YIELD POTENTIAL; FIELD EXPERIMENTAL DATA; CROP MODEL ENSEMBLE; SIMULATIONS
Resumen:
Grain production must increase by 60% in the next four decades to keep up with the expected population growth and food demand. A significant part of this increase must come from the improvement of staple crop grain yield potential. Crop growth simulation models combined with field experiments and crop physiology are powerful tools to quantify the impact of traits and trait combinations on grain yield potential which helps to guide breeding towards the most effective traits and trait combinations for future wheat crosses. The dataset reported here was created to analyze the value of physiological traits identified by the International Wheat Yield Partnership (IWYP) to improve wheat potential in high - yielding environments. This dataset consists of 11 growing seasons at three high - yielding locations in Buenos Aires (Argentina), Ciudad Obregon (Mexico), and Valdivia (Chile) with the spring wheat cultivar Bacanora and a high - yielding genotype selected from a doubled haploid (DH) population developed from the cross between the Bacanora and Weebil cultivars from the International Maize and Wheat Improvement Center (CIMMYT). This dataset was used in the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Phase 4 to evaluate crop model performance when simulating high - yielding physiological traits and to determine the potential production of wheat using an ensemble of 29 wheat crop models. The field trials were managed for non - stress conditions with full irrigation, fertilizer application, and without biotic stress. Data include local daily weather, soil characteristics and initial soil conditions, cultivar information, and crop measurements (anthesis and maturity dates, total above - ground biomass, final grain yield, yield components, and photosynthetically active radiation interception). Simulations include both daily in - season and end - of - season results for 25 crop variables simulated by 29 wheat crop models.
Citación:
---------- APA ----------
Guarin, J. R.; Martre, P.; Ewert, F.; Webber, H.; Dueri, S.; Calderini, D. F.; Reynolds, M. P.; Miralles, D. J. & García, G. A. (2023).A high - yielding traits experiment for modeling potential production of wheat : field experiments and AgMIP - Wheat multi - model simulations.Open Data Journal for Agricultural Research,9,p.26-33
10.18174/odjar.v9i0.18573
---------- CHICAGO ----------
Guarin, José Rafael,Martre, Pierre,Ewert, Frank,Webber, Heidi,Dueri, Sibylle,Calderini, Daniel Fernando, et al..2023. "A high - yielding traits experiment for modeling potential production of wheat : field experiments and AgMIP - Wheat multi - model simulations".Open Data Journal for Agricultural Research 9:26-33.
Recuperado de http://ri.agro.uba.ar/greenstone3/library/collection/arti/document/2023guarin