Nitrogen (N) fertilizer decision support systems that rely primarily on corn grain yield often perform poorly because year-to-year variations in net soil N supply are not considered. However, there are environments where N mineralization and N losses are stable from year-to-year while variations in economically optimum N rates (EONR) are large. In such environments, interannual variations in EONR would be explained mainly by variation in yield, and weather effects on yield formation would be more important for EONR determination than weather effects on N cycling processes that govern N mineralization and loss. Data from a 10-year continuous corn N fertilization study (2009–2018) in Elora, Ontario, Canada were used to investigate the determinants of EONR in an environment with low and interannually stable N supply. EONR varied significantly over the study period, ranging between 157 and 273 kg N ha⁻¹. Corn N uptake at maturity in check plots did not vary significantly over time, indicating stable soil N supply. Overwinter N losses effectively reset soil N supply to a baseline each season. Maximum economic yield was strongly correlated to EONR (R² = 0.65). Most of the variability in the EONR could be explained by rainfall during V5-V12 (R² = 0.84) and solar radiation during VT-R1 (R² = 0.64), suggesting weather influenced EONR primarily by influencing crop N demand. Since grain yield can explain a large proportion of interannual variation in EONR, N rate recommendation systems should not ignore yield predictions, and greater efforts should be made to increase yield prediction accuracy.

主要依赖玉米产量的氮 (N) 肥料决策支持系统通常表现不佳，因为没有考虑净土壤 N 供应的逐年变化。然而，在某些环境中，N 矿化和 N 损失逐年稳定，而经济最佳 N 率 (EONR) 的变化很大。在这样的环境中，EONR 的年际变化将主要由产量的变化来解释，对于 EONR 的确定，天气对产量形成的影响比天气对控制 N 矿化和流失的 N 循环过程的影响更为重要。来自加拿大安大略省埃洛拉市一项为期 10 年的连续玉米施氮研究（2009-2018）的数据被用于调查在氮供应量低且年际稳定的环境中 EONR 的决定因素。^-1。对照样地成熟时玉米 N 吸收量没有随时间显着变化，表明土壤 N 供应稳定。越冬氮损失有效地将土壤氮供应重置为每个季节的基线。最大经济收益与 EONR 密切相关（R ²  = 0.65）。EONR 的大部分变化可以用 V5-V12 期间的降雨量 ( R ²  = 0.84) 和 VT-R1 期间的太阳辐射 ( R ²  = 0.64) 来解释，这表明天气主要通过影响作物 N 需求来影响 EONR。由于谷物产量可以解释 EONR 年际变化的很大一部分，N 率推荐系统不应忽视产量预测，应加大力度提高产量预测精度。