Abstract

Future climate changes can have a major impact on crop production. But, whatever the climatic changes, crop production can be adapted to climate change by implementing alternative management practices and developing new genotypes that will take full advantage of the future climatic conditions. Since the classical agronomic research approach is not possible in identifying these new agronomic technologies for the future climatic conditions, we used response surface methodology (RSM) in connection with the CERES-Wheat crop model and the HADCM2 climate simulation model to identify optimal configuration of plant traits and management practices that maximize yield of winter wheat under high CO2 environments. The simulations were conducted for three Nebraska locations (Havelock, Dickens and Alliance), which were considered representative of winter wheat growing areas in the central Great Plains. At all locations, the identified optimal winter wheat cultivar under high CO2 conditions had a larger number of tillers, larger kernel size, shorter days to flower, grew faster and had more kernels per square meter than the check variety under normal CO2 conditions, while the optimal planting dates were later and planting densities were lower than under normal conditions. We concluded that RSM used in conjunction with crop and climate simulation models was a useful approach to understanding the complex relationship between wheat genotypes, climate and management practices.

Keywords

Response surface methodology, steepest ascent, global climate change, CERES-Wheat model, high CO2 conditions

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Apr 28th, 3:15 PM

SIMULATION AND RESPONSE SURFACE METHODOLOGY TO OPTIMIZE WINTER WHEAT RESPONSE TO GLOBAL CLIMATE CHANGE

Future climate changes can have a major impact on crop production. But, whatever the climatic changes, crop production can be adapted to climate change by implementing alternative management practices and developing new genotypes that will take full advantage of the future climatic conditions. Since the classical agronomic research approach is not possible in identifying these new agronomic technologies for the future climatic conditions, we used response surface methodology (RSM) in connection with the CERES-Wheat crop model and the HADCM2 climate simulation model to identify optimal configuration of plant traits and management practices that maximize yield of winter wheat under high CO2 environments. The simulations were conducted for three Nebraska locations (Havelock, Dickens and Alliance), which were considered representative of winter wheat growing areas in the central Great Plains. At all locations, the identified optimal winter wheat cultivar under high CO2 conditions had a larger number of tillers, larger kernel size, shorter days to flower, grew faster and had more kernels per square meter than the check variety under normal CO2 conditions, while the optimal planting dates were later and planting densities were lower than under normal conditions. We concluded that RSM used in conjunction with crop and climate simulation models was a useful approach to understanding the complex relationship between wheat genotypes, climate and management practices.