Optimum size in grid soil sampling for variable rate application in site-specific management
Optimum size in grid soil sampling for variable rate application in site-specific management
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DOI：
10.1590/s0103-90162011000300017
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发表时间：
2011-06-01
影响因子：
2.6
通讯作者：
Cezar, Everson
中科院分区：
文献类型：
--
作者：
Nanni, Marcos Rafael;Povh, Fabrício Pinheiro;Cezar, Everson
了解土壤空间变异的重要性与作物管理规划有关。这种认识使我们能够将土壤视为一个可变的实体，而不是一个统一的实体，并使针对具体地点的管理能够提高生产效率，这是精确农业的目标。问题仍然是最佳的土壤采样间隔需要在巴西的网站特定的肥料建议。本研究的目的是：i）使用以不同分辨率的网格模式排列的地理参考土壤样本，评估影响施肥建议的主要属性的空间变异性; ii）将生成的空间图与使用1个样本公顷（-1）的标准采样获得的空间图进行比较，以验证空间分辨率的适当性。评价的属性包括磷（P）、钾（K）、有机质（OM）、盐基饱和度（V%）和粘粒。土壤样本收集在100 x 100米的地理参考网格中。进行间伐以创建网格，每2.07、2.88、3.75和7.20公顷一个样品。地质统计学技术，如半变异函数和插值克里金，被用来分析属性在不同的网格分辨率。该分析使用Vesper软件包进行。使用kappa统计量比较通过该方法创建的图。此外，通过使用交叉验证将观察值与估计值作图绘制相关图。P、K和V%，需要比使用1公顷样本的采样分辨率更精细的采样分辨率，而对于有机质和粘土，分别每两公顷和三公顷一个样本的较粗分辨率可能是可以接受的。
The importance of understanding spatial variability of soils is connected to crop management planning. This understanding makes it possible to treat soil not as a uniform, but a variable entity, and it enables site-specific management to increase production efficiency, which is the target of precision agriculture. Questions remain as the optimum soil sampling interval needed to make site-specific fertilizer recommendations in Brazil. The objectives of this study were: i) to evaluate the spatial variability of the main attributes that influence fertilization recommendations, using georeferenced soil samples arranged in grid patterns of different resolutions; ii) to compare the spatial maps generated with those obtained with the standard sampling of 1 sample ha(-1), in order to verify the appropriateness of the spatial resolution. The attributes evaluated were phosphorus (P), potassium (K), organic matter (OM), base saturation (V%) and clay. Soil samples were collected in a 100 x 100 m georeferenced grid. Thinning was performed in order to create a grid with one sample every 2.07, 2.88, 3.75 and 7.20 ha. Geostatistical techniques, such as semivariogram and interpolation using kriging, were used to analyze the attributes at the different grid resolutions. This analysis was performed with the Vesper software package. The maps created by this method were compared using the kappa statistics. Additionally, correlation graphs were drawn by plotting the observed values against the estimated values using cross-validation. P, K and V%, a finer sampling resolution than the one using 1 sample ha is required, while for OM and clay coarser resolutions of one sample every two and three hectares, respectively, may be acceptable.