Wheat biomass sensitivity analysis apsim
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Consequently, analyzing the radar backscatter characteristics of wheat has become an active research field in recent years.
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Wheat, as the second main crop in the world, is closely related to food security, economic development, and societal stability. Microwave remote sensing has been a popular tool because of the distinct benefits such as retrieval of vegetation information, penetrability, and availability in all weathers. Furthermore, it was concluded that wheat ears should form an essential component of theoretical modeling as they influence the final yield. The research results showed that the biomass retrieved from the advanced synthetic aperture radar (ASAR) images to agree well with the data measured in situ after setting the modified water-cloud model for the growth stages with ears. This work presents two retrieval models based on the water-cloud model and adopts the advanced integral equation model to simulate the soil backscatter before the heading stage and the backscatter from the layer under wheat ears after the heading stage. Wheat ears have been demonstrated to have a great influence on radar backscatter therefore, a modified version of water-cloud model used for retrieving biomass should consider the effect of wheat ears. Simultaneously, parameters such as wheat and soil characteristics as well as volume scattering and soil scattering were analyzed for the two periods during the entire growth cycle. Since wheat ears are related to wheat growth and yield, the radar backscatter of wheat was analyzed at two different periods, i.e., with and without wheat ears. Program-West and Central Africa for Dryland Cereal.This article presents an analysis of the scattering measurements for an entire wheat growth cycle by ground-based scatterometers at a frequency of 5.3 GHz. The experiment was conducted under the former CG research Nigeria for providing institutional support for the study. The authors would like to thank the InternationalĬrop Research Institute for Semi-Arid Tropics (ICRISAT), Item Type:ĬGIAR Research Program on Dryland CerealsĬrop simulation model, photoperiod insensitive, sorghum, rainfall, temperature Thus, climate-smart site-specific utilization of the photoperiod insensitive sorghum cultivar suggests more resilient and productive farming systems for sorghum in semi-arid regions of Mali. However, the magnitude of temperature changes showed a decline in grain yield by 10%, while a decrease in rainfall by W-25% and W-50% resulted in yield decline between 5% and 37%, respectively. Simulations at varying Nfertilizer application rate with increased temperature of 2 ☌, 4 ☌ and 6 ☌ and decreased rainfall by 25 and 50 % (W-25% and W-50%) posed a highly significant risk to low yield compared to increase in rainfall. Total biomass and grain yield were satisfactorily reproduced, indicating fairly low RMSE values of 21.3% for total biomass and very low RMSE of 11.2 % for grain yield of the observed mean. The results showed that model performance was excellent with the lowest mean bias error (MBE) of -2.2 days for flowering and 1.4 days for physiological maturity.
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Following model calibration of the cultivar at varying sowing dates over two growing seasons (20), a long-term simulation was run using historical weather data (1981-2010) to determine the impacts of temperature and rainfall on grain yield, total biomass and water use efficiency at varying nitrogen fertilizer applications.
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WHEAT BIOMASS SENSITIVITY ANALYSIS APSIM SIMULATOR
Moench) using the Agricultural Production Systems Simulator (APSIM) In this study, the response of temperature and rainfall to yield patterns of photoperiod insensitive sorghum (Sorghum bicolor L. Journal of Agrometeorology (TSI), 21 (3).Ī combination of local-scale climate and crop simulation model were used to investigate the impacts of change in temperature and rainfall on photoperiod insensitive sorghum in the Sudanian zone of Mali. Impacts of rainfall and temperature on photoperiod insensitive sorghum cultivar : model evaluation and sensitivity analysis. Akinseye, F M and Folorunsho, A H and Ajeigbe, H A and Agele, S O