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首页> 外文期刊>Frontiers in Plant Science >A Vision for Incorporating Environmental Effects into Nitrogen Management Decision Support Tools for U.S. Maize Production
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A Vision for Incorporating Environmental Effects into Nitrogen Management Decision Support Tools for U.S. Maize Production

机译:将环境影响纳入美国玉米生产氮管理决策支持工具的愿景

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Meeting crop nitrogen (N) demand while minimizing N losses to the environment has proven difficult despite significant field research and modeling efforts. To improve N management, several real-time N management tools have been developed with a primary focus on enhancing crop production. However, no coordinated effort exists to simultaneously address sustainability concerns related to N losses at field- and regional-scales. In this perspective, we highlight the opportunity for incorporating environmental effects into N management decision support tools for United States maize production systems by integrating publicly available crop models with grower-entered management information and gridded soil and climate data in a geospatial framework specifically designed to quantify environmental and crop production tradeoffs. To facilitate advances in this area, we assess the capability of existing crop models to provide in-season N recommendations while estimating N leaching and nitrous oxide emissions, discuss several considerations for initial framework development, and highlight important challenges related to improving the accuracy of crop model predictions. Such a framework would benefit the development of regional sustainable intensification strategies by enabling the identification of N loss hotspots which could be used to implement spatially explicit mitigation efforts in relation to current environmental quality goals and real-time weather conditions. Nevertheless, we argue that this long-term vision can only be realized by leveraging a variety of existing research efforts to overcome challenges related to improving model structure, accessing field data to enhance model performance, and addressing the numerous social difficulties in delivery and adoption of such tool by stakeholders.
机译:尽管进行了大量的田间研究和建模工作,但要满足作物氮(N)的需求同时最大程度地减少对环境的氮损失已被证明是困难的。为了改善氮素管理,已经开发了几种实时氮素管理工具,其主要重点是提高作物产量。但是,不存在协调一致的努力来同时解决与田间和区域规模的氮损失有关的可持续性问题。从这个角度来看,我们强调了将环境影响纳入美国玉米生产系统的N种管理决策支持工具的机会,方法是将公开可用的作物模型与种植者输入的管理信息以及网格化土壤和气候数据整合到专门用于量化的地理空间框架中环境与作物生产之间的权衡。为了促进该领域的发展,我们评估了现有作物模型提供季节性N建议的能力,同时估算了N淋失和一氧化二氮的排放,讨论了初始框架开发的几个注意事项,并着重指出了与提高作物准确性有关的重要挑战模型预测。这样的框架将有助于确定N个损失热点,从而有利于区域可持续集约化战略的发展,这些热点可用于实施与当前环境质量目标和实时天气状况有关的空间明确缓解措施。然而,我们认为,只有通过利用各种现有研究成果来克服与改善模型结构,访问实地数据以增强模型性能以及解决交付和采用模型时遇到的众多社会难题有关的挑战,才能实现这一长期愿景。利益相关者的这种工具。

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