Modeling temperature response in wheat and maize
Modeling temperature response in wheat and maize
- Mexico : CIMMYT, 2003.
- vi, 53 pages
- CIMMYT NRG-GIS Series ; 03-01 1405-7484 .
Open Access
During the workshop “Modeling Temperature Response in Wheat and Maize,” held from 23 to 25 April 2001 at CIMMYT’s headquarters at El Batan, Mexico, participants examined various approaches for modeling temperature effects in crops. Effects on both growth and development were considered. A review of the FORTRAN code of the CERES models by Wilkens and Singh showed how temperature is thought to influence numerous processes, including carbohydrate production, growth, soil nitrogen dynamics, root growth and evapotranspiration. The effect of temperature on grain nitrogen filling rate showed an unexpected discontinuity, which merits further investigation. It was suggested that the software code be modified to allow greater flexibility in modifying temperature functions. This would facilitate testing of proposed model improvements. White and Reynolds reviewed the expected temperature responses that crop models typically consider: development (including phenology and morphology), photosynthesis, respiration, partitioning, and to a lesser extent, nutrient uptake. Emphasis was given to the need to distinguish between immediate responses and acclimation effects, and to use realistic growing conditions. In an experiment where wheat was subjected to different soil temperatures, McMaster and Hunt found that while increased soil temperature accelerated germination, soil temperature had no effect on subsequent development. The authors proposed that since meristematic regions in the shoot occur in various locations (i.e., apical meristem, internodes, and leaf sheath) and are subject to distinct thermal regimes, air temperature may have a greater effect on development than was previously expected. CERES-Maize currently does not simulate tiller production as found at low populations. Du Toit and Prinsloo compared three approaches for modeling tiller production, including two that consider temperature and photoperiod effects. During the working groups, wheat modelers focused on reviewing modeling response to planting dates for winter-sown spring wheats, using the data sets of S.S. Dhillon from Ludhiana, India for validation. The work was continued following the workshop and showed that both CERES-Wheat 3.5 and Sirius had difficulties simulating vernalization under the relatively warm conditions prevailing at Ludhiana. To facilitate model validation and adaptation in the Highveld Ecoregion Project, two software packages were developed by Du Toit and Du Toit. The Model Statistical Package uses standard outputs of CERES-Maize 3.0 to calculate linear regression statistics (slope, intercept, and r2), D-index, and the systematic and unsystematic mean square errors. The Weather Analogue Program allows users to create mid-season projections of crop performance based on five sets of historical data showing the greatest similarity to the ongoing season. The Model Statistical Package was demonstrated during the working group and was found to be very promising for rapid assessment of model performance. During the inaugural meeting of the Global Change and Terrestrial Ecosystem (GCTE) Tropical Cereals Network, participants reviewed models available for maize, sorghum and millet and identified possible sources of data for model evaluation. Plans for subsequent activities of the Network were outlined.
Text in English
1405-7484
Crop yield
Maize
Simulation models
Temperature
Wheat
Soil temperature
Soil water balance
Nitrogen metabolism
Soil transport processes
Environmental factors
Thermal analysis
Photoperiodicity
Statistical data
Open Access
During the workshop “Modeling Temperature Response in Wheat and Maize,” held from 23 to 25 April 2001 at CIMMYT’s headquarters at El Batan, Mexico, participants examined various approaches for modeling temperature effects in crops. Effects on both growth and development were considered. A review of the FORTRAN code of the CERES models by Wilkens and Singh showed how temperature is thought to influence numerous processes, including carbohydrate production, growth, soil nitrogen dynamics, root growth and evapotranspiration. The effect of temperature on grain nitrogen filling rate showed an unexpected discontinuity, which merits further investigation. It was suggested that the software code be modified to allow greater flexibility in modifying temperature functions. This would facilitate testing of proposed model improvements. White and Reynolds reviewed the expected temperature responses that crop models typically consider: development (including phenology and morphology), photosynthesis, respiration, partitioning, and to a lesser extent, nutrient uptake. Emphasis was given to the need to distinguish between immediate responses and acclimation effects, and to use realistic growing conditions. In an experiment where wheat was subjected to different soil temperatures, McMaster and Hunt found that while increased soil temperature accelerated germination, soil temperature had no effect on subsequent development. The authors proposed that since meristematic regions in the shoot occur in various locations (i.e., apical meristem, internodes, and leaf sheath) and are subject to distinct thermal regimes, air temperature may have a greater effect on development than was previously expected. CERES-Maize currently does not simulate tiller production as found at low populations. Du Toit and Prinsloo compared three approaches for modeling tiller production, including two that consider temperature and photoperiod effects. During the working groups, wheat modelers focused on reviewing modeling response to planting dates for winter-sown spring wheats, using the data sets of S.S. Dhillon from Ludhiana, India for validation. The work was continued following the workshop and showed that both CERES-Wheat 3.5 and Sirius had difficulties simulating vernalization under the relatively warm conditions prevailing at Ludhiana. To facilitate model validation and adaptation in the Highveld Ecoregion Project, two software packages were developed by Du Toit and Du Toit. The Model Statistical Package uses standard outputs of CERES-Maize 3.0 to calculate linear regression statistics (slope, intercept, and r2), D-index, and the systematic and unsystematic mean square errors. The Weather Analogue Program allows users to create mid-season projections of crop performance based on five sets of historical data showing the greatest similarity to the ongoing season. The Model Statistical Package was demonstrated during the working group and was found to be very promising for rapid assessment of model performance. During the inaugural meeting of the Global Change and Terrestrial Ecosystem (GCTE) Tropical Cereals Network, participants reviewed models available for maize, sorghum and millet and identified possible sources of data for model evaluation. Plans for subsequent activities of the Network were outlined.
Text in English
1405-7484
Crop yield
Maize
Simulation models
Temperature
Wheat
Soil temperature
Soil water balance
Nitrogen metabolism
Soil transport processes
Environmental factors
Thermal analysis
Photoperiodicity
Statistical data