• Peer-reviewed, scientific manuscripts will be developed as appropriate documenting responses to planting date, latitude, and environmental factors for MG 3 to 6 of yield, phenology, seed oil and protein concentrations, seed grade, standard and accelerated aging germination.
• Peer-reviewed, scientific manuscripts will be developed as appropriate on economic analyses from this data set.
• Peer-reviewed, scientific manuscripts will be developed as appropriate from the long-term simulation results from DSSAT-CropGro on yield, crop phenology, and irrigation requirements and how these factors affect profitability and risk of crop production.
• From peer-reviewed manuscripts, we will develop producer-friendly fact sheets that will be made available to USB and MSSB for their use on their websites as they deem appropriate.
• From the DSSAT-CropGro simulations, we will develop a decision-support tool for producers that will aid in MG selection for their location and desired planting date.
• After the project is completed, the entire data base will be made freely available to the soybean community for their use.

• 90% of seed grade analysis completed
• 40% of tests for germination and accelerated aging completed
• 80% of oil and protein analysis completed
• Preparation of dataset with yield, during season notes, and phenology data for the 3-yr study.
• Calculate environmental variables during key developmental stages and incorporation into dataset.
• Study of the relationship between yield and cumulative intercepted photosynthetically active radiation
• Evaluation of model performance by location and treatment
• Preparation of DSSAT-GLUE to perform calibrations using the high performance computing facilities at the University of Arkansas.
• Study of MG and planting dates that maximize the fraction of light interception and total cumulative photosynthetically active radiation at two contrasting locations in Arkansas.
• Long term weather datasets were generated for a total of 11 locations.
• Preparation of necessary simulation files to simulate the complete range of scenarios.
• Generation of a preliminary dataset that contains all necessary information for the development of the decision tool.
• Development of the Excel interface for the decision tool.
• Incorporation of preliminary agronomic and economic databases to the decision tool.