Management zones (MZs) are delineated areas within an agricultural field with relatively homogenous soil properties, and therefore similar crop fertility requirements. Consequently, such MZs can often be used for site-specific management of crop production inputs. This study evaluated the effectiveness of four classification methods for delineating MZs in an 8-ha commercial potato field located in Prince Edward Island, Canada. The apparent electrical conductivity (EC_a) at two depths from a commercial Veris sensor were used to delineate MZs using three classification methods without spatial constraints (i.e., fuzzy k-means, ISODATA and hierarchical) and one with spatial constraints (i.e., spatial segmentation method). Soil samples (0.0–0.15 m depth) from 104 sampling points was used to measure soil physical and chemical properties and their spatial variation in the field were used as reference data to evaluate four delineation methods. Significant Pearson correlations between EC_a and soil properties were obtained (0.22 < r < 0.85). The variance reduction indicated that two to three MZs were optimal for representing the field’s spatial variability of soil properties. For two MZs, most soil physical and chemical properties differed significantly between MZs for all four delineation methods. For three MZs, there was greater discrimination among MZs for several soil properties for the spatial segmentation-based method compared with other delineation methods. Moreover, consideration of the spatial coordinates of the data improved the delineation of MZs and thereby increased the number of significant differences among MZs for individual soil properties. Therefore, the spatial segmentation method had the greatest efficiency in delineation of MZs from statistical and agronomic perspectives.

中文翻译：

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分析四种确定加拿大东部商业马铃薯田潜在管理区的方法

管理区（MZs）是农田内具有相对均一的土壤特性的划定区域，因此对作物的肥力要求相似。因此，此类MZ通常可用于作物生产投入的特定地点管理。这项研究评估了在加拿大爱德华王子岛一个8公顷的商业马铃薯田中划定MZ的四种分类方法的有效性。表观电导率（EC _a）从商用Veris传感器的两个深度处使用三种无空间约束的分类方法（即，模糊k均值，ISODATA和分层）和一种具有空间约束的分类方法（即，空间分割方法）来描绘MZ。使用104个采样点的土壤样品（深度0.0-0.15 m）来测量土壤的理化性质，并将其在田间的空间变化作为参考数据来评估四种描述方法。EC _a之间的显着Pearson相关性获得了土壤特性（0.22 <r <0.85）。方差减少表明，两到三个MZ最适合代表田间土壤特性的空间变异性。对于两种MZ，在所有四种划定方法下，大多数MZ之间的土壤理化性质都存在显着差异。对于三个MZ，与其他划界方法相比，基于空间分割的方法在MZ中对几种土壤属性的区分更大。此外，数据空间坐标的考虑改善了MZ的轮廓，从而增加了各个土壤属性的MZ之间的显着差异数量。因此，从统计学和农艺学的角度来看，空间分割方法在描绘MZ方面效率最高。