Understanding yield potential and yield-limiting factors is essential for improving profitability and grain yields while avoiding adverse environmental effects. In the USA, grain yield monitors are widely used but the information they provide is rarely used to understand within-field yield variations and associated yield constraints. The objectives of this research were to understand the influence of in-season precipitation on within-field spatio-temporal variation of maize (Zea mays L.) yield and to determine manageable yield variation in two contrasting Major Land Resource Areas of the Mid-Atlantic USA. It does this by assessing the association of grain yield monitor data and in-season precipitation information to be used for variable rate management. Maize yields, as evaluated by baseline functions, were more closely associated with in-season precipitation in the Coastal Plain than in the Piedmont. The study then used standardized principal component analysis (stdPCA) to reveal within-field yield patterns. These varied only under moisture-limited conditions in the Coastal Plain. In the Piedmont, the within-field yield pattern was more consistent under a range of in-season precipitation conditions. In Coastal Plain rainfed fields, the yield predictability increased at the end of June, indicating the possibility of predicting within-field spatial patterns in mid-season. These approaches were successful in deciding whether within-field site- and time-specific management is beneficial for a particular region or field. The presented method, combining stdPCA and geostatistical assessment, is useful in strategizing precision crop management, but do not reveal causes. Detailed soil information and topography could additionally be valuable for understanding constraints to crop yield.

了解产量潜力和产量限制因素对于提高盈利能力和谷物产量同时避免不利的环境影响至关重要。在美国，谷物产量监测器被广泛使用，但它们提供的信息很少用于了解田间产量变化和相关的产量限制。本研究的目的是了解季节性降水对玉米田间时空变化的影响（Zea maysL.) 产量并确定美国中大西洋两个对比鲜明的主要土地资源区的可管理产量变化。它通过评估谷物产量监测数据和用于可变速率管理的季节性降水信息的关联来实现这一点。根据基线函数的评估，与皮埃蒙特相比，沿海平原的玉米产量与季节性降水的关系更为密切。然后，该研究使用标准化主成分分析 (stdPCA) 来揭示田间产量模式。这些仅在沿海平原的水分有限条件下发生变化。在皮埃蒙特，在一系列季节性降水条件下，田间产量模式更加一致。在沿海平原雨养田，6 月底产量可预测性增加，表明在季节中期预测场内空间模式的可能性。这些方法成功地决定了现场特定地点和特定时间的管理是否对特定区域或领域有益。所提出的方法，结合 stdPCA 和地统计评估，可用于制定精确的作物管理战略，但不会揭示原因。详细的土壤信息和地形对于了解作物产量的限制也很有价值。