A high-yielding traits experiment for modeling potential production of wheat: field experiments and AgMIP-Wheat multi-model simulations
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 cro...
| Autores: | , , , , , , , , , , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Universitat de Lleida (UdL) |
| Repositorio: | Repositori Obert UdL |
| OAI Identifier: | oai:repositori.udl.cat:10459.1/467906 |
| Acceso en línea: | https://doi.org/10.18174/odjar.v9i0.18573 https://hdl.handle.net/10459.1/467906 |
| Access Level: | acceso abierto |
| Palabra clave: | Wheat Yield potential Field experimental data Crop model ensemble Simulations |
| Sumario: | 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 potentialwhich helpsto guide breeding towards the most effective traits and trait combinations for future wheat crosses. The dataset reported herewas created to analyzethe value of physiological traits identified by the International Wheat Yield Partnership (IWYP)to improve wheat potential in high-yielding environments. This dataset consists of11growing 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 theBacanora and Weebil cultivars from theInternational Maize and Wheat Improvement Center(CIMMYT). Thisdataset 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 wheatusing an ensemble of 29 wheat crop models. The field trialswere 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 photosyntheticallyactive radiationinterception). Simulations include both daily in-season and end-of-season results for25crop variables simulated by 29wheat crop models. |
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