Reducing the decision-making unit to classes within fields can improve yields, efficiency in the use of nutrients and profitability of crops. The objectives were to compare methods for class delimitation in wheat (Triticum aestivum L.) crops based on apparent productivity levels and establish similarities among them in terms of spatial overlapping, productive attributes and the use of nitrogen. In three wheat fields, high and low apparent productivity classes (APC) were defined based on eight methodologies: yield maps, soil maps, gramineae vegetation index, rotation crop index, interpretation of satellite images, management records, elevation and integrated soil and yield maps. In each APC, soil and crop yield components were determined under five nitrogen fertilization levels. Among delimitation methodologies, the degree of coincidence varied from 1.4 to 81.7%. The differences in soil properties, nitrogen use efficiency and grain yields were greater among fields than among APC within each field. In each field, the delimitation methodologies identified different single factors that discriminated among the potential management classes and were partially associated with the crop grain yields. The wheat crops at the low APC yielded 39% less and 12% less than at the high APC, respectively. The nitrogen fertilization, at the rate for maximum productivity for each ACP, reduced the yield differences between contrasting APC. Nitrogen fertilization also modified clustering of classes based on expected yields. Making management classes for wheat based on expected productivity is more accurate when based on previous crop production information under similar nitrogen fertilization conditions than the targeted crop.

将决策单位减少到田间等级可以提高产量、养分利用效率和作物的盈利能力。目的是比较小麦 ( Triticum aestivumL.) 基于表观生产力水平的作物，并在空间重叠、生产属性和氮的使用方面建立它们之间的相似性。在三个麦田中，高低表观生产力等级 (APC) 基于八种方法进行定义：产量图、土壤图、禾本科植物指数、轮作作物指数、卫星图像解释、管理记录、海拔以及综合土壤和产量图. 在每个 APC 中，土壤和作物产量成分是在五个氮肥水平下确定的。在划界方法中，重合度从 1.4% 到 81.7% 不等。田间土壤性质、氮素利用效率和粮食产量的差异大于各田间APC之间的差异。在每个领域，划界方法确定了不同的单一因素，这些因素区分了潜在的管理类别，并且与作物谷物产量部分相关。低 APC 的小麦产量分别比高 APC 低 39% 和 12%。以每个 ACP 的最大生产力的速率施氮，减少了对比 APC 之间的产量差异。施氮肥还根据预期产量修改了类别的聚类。当基于类似施氮条件下的先前作物生产信息而不是目标作物时，根据预期生产力对小麦进行管理分类更为准确。低 APC 的小麦产量分别比高 APC 低 39% 和 12%。以每个 ACP 的最大生产力的速率施氮，减少了对比 APC 之间的产量差异。施氮肥还根据预期产量修改了类别的聚类。当基于类似施氮条件下的先前作物生产信息而不是目标作物时，根据预期生产力对小麦进行管理分类更为准确。低 APC 的小麦产量分别比高 APC 低 39% 和 12%。以每个 ACP 的最大生产力的速率施氮，减少了对比 APC 之间的产量差异。施氮肥还根据预期产量修改了类别的聚类。当基于类似施氮条件下的先前作物生产信息而不是目标作物时，根据预期生产力对小麦进行管理分类更为准确。