Simulating Soybean Yield Potential under Optimum Management

Abstract

Core Ideas: Soybean yield and crop growth was measured in high-yield contest fields. Radiation use efficiency and nitrogen uptake were greater than recorded values. Yield was grossly under-predicted using default growth parameters. Yield predictions were greatly improved using measured growth parameters. Crop models have played important roles in identifying potential constraints for crop growth and yield. A relatively simple soybean [Glycine max (L.) Merr.] model consisting of a daily C, N, and water budget was used to simulate yields for optimum production environments at Fayetteville, AR, and at a farmer's contest field in Missouri for 2012 to 2013. Data were collected on radiation use efficiency (RUE), N accumulation rate, specific leaf nitrogen (SLN), and the dry matter accumulation coefficient (DMAC) as a measure of whole-crop seed growth rate. In Fayetteville, measured yields ranged from 4977 to 7144 kg ha−1, and simulated yields averaged 34.0% below the measured yields using the default model parameters. Using measured parameters in a modified model, predicted yields were 2.8% above observed. Default parameter simulations for the contest fields were 39.0% below measured yield and were 18.7% below measured yield when using measured parameters. Sensitivity analyses indicated that lower DMAC values increased yields due to slower seedfill rates, allowing additional N accumulation and a slower translocation of N to the growing seeds. Simulating an increased SLN and RUE increased predicted yields in 2012 and 2013 when N accumulation rates were great enough to supply the required N for new biomass. Alternatively, increasing N accumulation rates increased yield up to a plateau when all N requirements were met. These results illustrate the importance and interconnectivity of the crop growth processes relating to C and N metabolism and that current bounds for crop growth characteristics should be reconsidered.