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They included asynchronous video content and four synchronous course periods with activities related to crop planting dates, water cycling with different crop rotations, fertilizer impacts on yield and environment, as well as a competition activity to optimize profit with. Mean ensemble model results showed reduced uncertainty for different crop parameter, especially the grain yield differences were reduced by 0.73-4.1% compared to observed yield. The team at University of Nebraska-Lincoln have utilized APSIM in a high enrolment undergraduate crop management course. If you are not an ASABE member or if your employer has not arranged for access to the full-text, Click here for options.
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Sensitivity analysis of both models showed that grain yield in CERES-Wheat was more sensitive to field capacity and in APSIM grain yield was quite sensitive to nitrogen application rate. Click on Download PDF for the PDF version or on the title for the HTML version. APSIM and CERES-Wheat during the evaluation simulated aboveground biomass, grain yield, LAI, canopy nitrogen, cumulative evapotranspiration, water use efficiency and nitrogen fertilizer productivity, and deviations from the observed were reasonable with nRMSE less than 21%. During calibration, APSIM grain yield was underestimated than CERES-Wheat while biomass and leaf area index was overestimated than CERES-Wheat model.
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APSIM and CERES-Wheat model calibration results of grain yield, biomass, and leaf area index varied between 1.4-14.1 % during three growing seasons.
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Experimental data was collected from a past study conducted in the same Guanzhong Plain where different irrigation and nitrogen levels treatments were tested during wheat growing season of 2009-2010, 12. Models performance was evaluated based on the criteria of statistical analysis including coefficient of determination (R 2), normalized root mean square error (nRMSE), and d-index. Crop models were calibrated by adopting standard procedure and protocols. In this study, two process based crop models APSIM and CERES-Wheat models were selected to determine their feasibility to simulate the wheat crop production in Guanzhong Plain in China by using calibration, evaluation and sensitivity analysis with experimental local data. These crop models are calibrated and evaluated before applying to a new geographical location. Cropping system models are considered useful tools to estimate the impact of climate and environment on agriculture production, and to improve the management of agricultural systems. Keywords: Calibration, Evaluation, Multiple crop models, Sensitivity analysis, Wheat yieldĪbstract. Joseph, Michigan Citation: 2019 ASABE Annual International Meeting 1900416.(doi:10.13031/aim.201900416)Īuthors: Qaisar Saddique, Jianmei Ji, Ali Ajaz, Xu Jiatun, Zou Yufeng, Jianqiang He, Huanjie Cai Published by the American Society of Agricultural and Biological Engineers, St. Performance Comparison of the APSIM and CERES-Wheat models in Guanzhong Plain, China Click on “Download PDF” for the PDF version or on the title for the HTML version.