Abstract Eco-efficient use of nitrogen (N) fertilizer in Corn (Zea Mays L.) requires timely information about the supply of N from the soil and the response to N by the crop. These are complex processes, and multiple N management strategies (NMS) have been proposed over time. In this work, we used APSIM (Agricultural Production Systems sIMulator) to simulate the response of Corn's Yield to N for ca. 4200 fields in the state of Illinois in different weather scenarios. Ten different N management strategies were evaluated using environmental and economic indicators. They were created by combining different sources of trial data, different types of prediction models, different predictor variables measured on the fields, and different technologies to apply fertilizer in the field. This study provides knowledge that is unattainable through field experimentation, leveraging current knowledge on the mechanisms that drive the yield response to N to help farmers, researchers, and policymakers to select strategies in line with their objectives. Our results showed that an N management strategy that incorporates year-to-year variability in the predictions and uses data from trials spread in the region achieved the highest eco-efficiency. Such strategy would reduce the mean N-leaching by 12.7% without changing profits compared with the N management strategy most used by extension services in the area. Nitrogen measurements obtained by soil sampling were the most important predictor and could not be replaced by other less laborious variables. Variable-rate technology did not provide significant economic or environmental value in the area.

中文翻译：

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伊利诺伊州玉米氮管理策略的经济和环境影响建模

摘要 玉米 (Zea Mays L.) 氮肥的生态高效利用需要及时了解土壤中氮的供应情况以及作物对氮的反应。这些都是复杂的过程，随着时间的推移，已经提出了多种 N 管理策略 (NMS)。在这项工作中，我们使用 APSIM（农业生产系统模拟器）来模拟玉米产量对 N 的响应。伊利诺伊州 4200 块不同天气情况下的田地。使用环境和经济指标评估了十种不同的氮管理策略。它们是通过结合不同的试验数据来源、不同类型的预测模型、在田间测量的不同预测变量以及在田间施肥的不同技术而创建的。本研究提供了通过田间试验无法获得的知识，利用当前关于驱动对 N 的产量响应的机制的知识，帮助农民、研究人员和决策者选择符合其目标的策略。我们的结果表明，在预测中包含逐年变化并使用来自该地区的试验数据的 N 管理策略实现了最高的生态效率。与该地区推广服务最常用的氮管理策略相比，这种策略将在不改变利润的情况下将平均氮浸出降低 12.7%。通过土壤取样获得的氮测量值是最重要的预测因子，不能被其他不太费力的变量取代。