The simulated data was generated using the APSIM soybean model (Robertson et al., 2001 Keating et al., 2003) and recently calibrated soybean varieties for the Midwest (Archontoulis et al., 2014). Version 1 of the decision tool contains both data simulated by a model and measured data. Within a location the user can select a soybean maturity (12 options) and a planting date (24 options) and visualize graphically the impact on yield and crop staging, as well as the optimum date of planting date and maturity group selection for maximum yields. The decision tool has the potential for use in Extension, teaching, and research and presently covers 11 geographic locations (Fig. A soybean planting decision support tool is presented here with the objective to assist in better understanding planting date by maturity by location interactions on soybean yield and crop staging.
Also, spring and early season weather sometimes forces farmers to replant soybeans later than ideal planting windows. Each year farmers are faced with the decision of planting into marginal conditions or the potential of late planting. An added complexity in the decision making is the weather conditions at the time of planting. Typically, soybean variety selection occurs months before soybean planting occurs. Australian Journal of Agricultural Research, 53: 429-446.Ĭhoosing soybean maturities and when to plant soybeans are two critical decisions that farmers make each year. Simulation of growth and development of diverse legume species in APSIM. Robertson MJ, Carberry PS, Huth NI, Turpin JE, Probert ME, Poulton PL, Bell M, Wright GC, Yeates SJ, Brinsmead RB, 2002.Iowa State University Extension and Outreach, Ames, Iowa. An overview of APSIM, a model designed for farming systems simulation.
Environmental Modeling & Software 62: 465–477 A methodology and an optimization tool to calibrate phenology of short-day species included in the APSIM PLANT model: application to soybean. Archontoulis SV, Miguez FE, Moore KJ, 2014.
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