Abstract
Improved prediction of optimal N fertilizer rates for corn (Zea mays L.) can reduce N losses and increase profits. We tested the ability of the Agricultural Production Systems sIMulator (APSIM) to simulate corn and soybean (Glycine max L.) yields, the economic optimum N rate (EONR) using a 16-year field-experiment dataset from central Iowa, USA that included two crop sequences (continuous corn and soybean-corn) and five N fertilizer rates (0, 67, 134, 201, and 268 kg N ha-1) applied to corn. Our objectives were to: (a) quantify model prediction accuracy before and after calibration, and report calibration steps; (b) compare crop model-based techniques in estimating optimal N rate for corn; and (c) utilize the calibrated model to explain factors causing year to year variability in yield and optimal N. Results indicated that the model simulated well long-term crop yields response to N (relative root mean square error, RRMSE of 19.6% before and 12.3% after calibration), which provided strong evidence that important soil and crop processes were accounted for in the model. The prediction of EONR was more complex and had greater uncertainty than the prediction of crop yield (RRMSE of 44.5% before and 36.6% after calibration). For long-term site mean EONR predictions, both calibrated and uncalibrated versions can be used as the 16-year mean differences in EONR’s were within the historical N rate error range (40–50 kg N ha-1). However, for accurate year-by-year simulation of EONR the calibrated version should be used. Model analysis revealed that higher EONR values in years with above normal spring precipitation were caused by an exponential increase in N loss (denitrification and leaching) with precipitation. We concluded that long-term experimental data were valuable in testing and refining APSIM predictions. The model can be used as a tool to assist N management guidelines in the US Midwest and we identified five avenues on how the model can add value toward agronomic, economic, and environmental sustainability.
Highlights
The economic optimum nitrogen (N) rate (EONR) is the fertilizer rate at which crop yield increase is not large enough to pay for additional N application, and more N would only result in unnecessary costs (Sawyer et al, 2006)
The CV decreased with increasing N rate in continuous corn (CC), but was consistent across N rate in soybean-corn rotation (SC)
We found that SOC prediction was insensitive to calibration when long-term mean crop yield was simulated well; (3) The optimum N rate was higher for CC than SC and according to the model analysis this is associated with higher SOC net mineralization in the SC rotation
Summary
The economic optimum nitrogen (N) rate (EONR) is the fertilizer rate at which crop yield increase is not large enough to pay for additional N application, and more N would only result in unnecessary costs (Sawyer et al, 2006). A number of approaches have been developed to predict optimal N application rates These include yield goal-based N recommendations and N budgets (Stanford, 1973, 1982; Stanford and Legg, 1984), pre-plant and pre-sidedress soil nitrate test (PPNT and PSNT, Bundy and Andraski, 1995; Shapiro et al, 2008), Illinois soil nitrogen test (ISNT, Mulvaney et al, 2001), crop canopy sensing (NDVI, Schmidt et al, 2009 and chlorophyll meter, Blackmer and Schepers, 1995; Varvel et al, 1997), and economic maximum return to N (MRTN, Sawyer et al, 2006). The above approaches have not fully resolved needed improvements from N management and gains in N use efficiency (Raun and Johnson, 1999; Fageria and Baligar, 2005) since N losses from corn-based systems are still high with negative environment impacts (Jaynes et al, 2001; Mitsch et al, 2001)
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