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Nitrogen decision making and the selection of the “right” N rate in wheat (Triticum aestivum L.) and maize (Zea mays L.) are difficult due to complex interactions in the N cycle with weather, management, and genetics. An adaptive management approach utilizing farmer networks and participatory learning was established to refine N rate decisions. On‐farm trials were established to reflect grower N rate with additional treatments of ±25% N. In 79 site‐years of wheat, N−25%, Nstd, and N+25% rate treatments were best in 37, 35, and 28% of the trials, respectively. In 100 site‐years of maize, N−25%, Nstd, and N+25% rate treatments were best in 58, 30, and 12% of the trials, respectively. Grower’s selected N rates in wheat were similar to recommendations from the North Carolina Realistic Yield Expectation (RYE) database while maize N rates were an average 48 kg ha−1 higher; however, N−25% rates, which were best 58% of the time, were similar to RYE N rate. Doppler‐based estimates of total precipitation from the National Weather Center explained 90% of the average maize yield variability. However, site‐yield was independent of location, N rate, and total precipitation. Measures of performance (N factor productivity and N balance) varied with achieved yields but indicate most growers apply N adequate to maintain organic N lost through mineralization. Results suggest that improved approaches to N rate selection and N efficiency will likely require in‐season adjustments to yield‐based N rates that incorporate local management and environmental conditions throughout the growing season. Core Ideas Yield level and response is independent of location, N rate, and total precipitation. Doppler‐based rainfall estimates help explain seasonal trends in yield. Growers often select N rates greater than recommended for maize but not wheat.
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Austin et al. (2019) studied this question.
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