Productivity of rainfed grain crops in Kentucky can be limited by water availability depending on precipitation patterns and the timing of critical crop developmental stages. Producers often need to address yield reductions due to water stress by increasing insurance costs, or compensate with years of greater yields. Adapting to earlier planting dates and/or different cultivar maturities could reduce the risk of yield losses due to water stress as well as increase yields under years of no water limitation. Moreover, developing site-specific diversification strategies or not putting all your eggs in the same basket could further reduce risk of yield losses and increase the overall farm net economic returns (i.e. planting 30% of acreage with a MG 3 cultivar in April, and the rest in May). Previous research in the U.S. Midsouth showed that soybean maturity group (MG) and planting date diversification strategies can greatly reduce risk of yield losses under irrigated conditions. The potential to increase productivity and yield stability under rainfed conditions in KY adapting to earlier planting dates or different MG cultivars, and by using diversifying management options, is expected to be much greater, but has not been quantified yet. This project will benefit soybean Kentucky farmers by generating yield responses across a wide range of planting dates and MG cultivars, and quantifying the yield limitation due to water stress. These are factors that play a major role in the determination of soybean yield on any given year and location, but that Kentucky farmers have currently limited information on. The outcomes from this project will provide site-specific management recommendations, as well as management diversification strategies that can increase economic returns under both rainfed and irrigated conditions.

Year 1: To conduct a planting date trial under irrigated and rainfed conditions, and with MG 2 to 5 soybeans in Lexington, KY.
NOTE: Optional planting date trial in Princeton submitted in separate proposal.
Year 2: To combine this data with other planting date x MG x Irrigation trials previously conducted by the PI to calibrate a predictive tool and generate a yield dataset across different locations, planting dates, MGs, and different soil and weather scenarios.
Year 3: To conduct an economic analysis and provide producers with site-specific planting date and maturity group
recommendations for irrigated and rainfed conditions, as well as management diversification strategies.

Findings from this project will be shared with producers in form of new and improved management recommendation guides that include the outcomes listed below (i.e. see Salmeron et al. in reference list). In addition, the data generated can be used to develop an interactive user-friendly decision tool for farmers (i.e. see SOYMAP and SOYRISK in reference list).
• Provide site-specific management adaptation choices (planting date x MG combination) that increases yield and economic returns under rainfed and under no water stress. These recommendations will be based on results that include planting dates from March to July, MG 2 to 5, and 7 locations across KY.
• Provide planting date and cultivar MG management adaptation strategies that consider different common soils in KY as well as soil depths.
• Identify site-specific diversification strategies (i.e. planting 20% of acreage in early April with MG 3 cultivars, and planting the rest in May with MG 4) that reduce risk and increase overall net economic returns.

Note to the KY Soybean Board: These 7 sites are the locations where the Soybean Performance Tests are conducted . Please communicate with the PI. Montse Salmeron (msalmeron@uky.edu) if you would like to see any additional location included to better characterize the range of environmental conditions in the state.

A planting date field trial was carried out successfully in 2020 under irrigated and rainfed
conditions, and with MG 2 to 5 soybeans. Data from planting date trials conducted in Lexington
during 2017 to 2020 were compiled and summarized in a draft manuscript by the graduate
student hired for this project. This draft manuscript identifies optimum cultivar MG choices for
planting dates in May and June under either irrigated and rainfed conditions, as well as the
yield decline with delay in planting date. In brief, under conditions of no water stress, soybean
yield would decrease by 2.8 bu ac-1 per week of delay in planting date (for MG 4 cultivars). The
yield response to planting date under rainfed conditions was more variable. Yield reductions
due to water limitation ranged anywhere from 0 to 37 bu ac-1 during the 2017 to 2020 growing
seasons. Yield losses due to water stress were greater for May planting dates compared to
June. These results suggest that while early planting dates may increase soybean yield
potential, the expected yield gain from advancing planting date may be limited in years of
insufficient precipitation. Similarly, we would expect deep soils with a high water retention
capacity to benefit more from planting in April, and require a full-season cultivar maturity to
achieve maximum yield potential. The graduate student expanded on this research by utilizing
the data to calibrate the DSSAT-CROPGRO model and explore a wider range of planting dates,
genotypes, locations, soil types, and irrigation management scenarios. This research is followed
up by a newly funded project to develop a management decision tool.

This project will benefit soybean Kentucky farmers by generating yield responses across a wide range of planting dates and MG cultivars, and quantifying the yield limitation due to water stress. These are factors that play a major role in the determination of soybean yield on any given year and location, but that Kentucky farmers have currently limited information on. The outcomes from this project will provide site-specific management recommendations, as well as management diversification strategies that can increase economic returns under both rainfed and irrigated conditions. These recommendations can be used to generate new and improved management recommendations guides (i.e. see Salmeron et al. in reference list), as well as an interactive decision tool (i.e. see SOYMAP and SOYRISK in reference list).