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Using low-cost geophysical survey to map soil properties and delineate management zones on grazed permanent pastures

机译:利用低成本地球物理调查来绘制土壤特性和放牧的永久性牧场的划分管理区

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Usually, soils utilised for livestock production have similar high spatial variability as those for agricultural or forest use. As a consequence, it is necessary to determine the spatial patterns of the main soil properties as the first stage to implement site-specific management. However, this has to be performed using an inexpensive technique because the profitability in these types of farm are very low, so owners need a cheap, effective, and reliable method to know which zones have similar production potential. Using soil apparent electrical conductivity (ECa) measurements, obtained with a contact sensor at many locations, as the basis to perform a directed soil sampling, 10 samples were taken at two depths (0-0.25 m and 0.25-0.50 m) in a 2.3 ha field in evora (southern Portugal). Firstly, relationships between ECa and many soil properties were analysed using regression analysis. Six soil properties (clay, silt, fine sand, soil moisture content, pH, and cation exchange capacity) were significantly correlated with ECa. Consequently, spatial distributions of these variables were visualised using map algebra techniques. Later, a fuzzy clustering algorithm was utilised to delineate management zones, resulting in two subfields to be managed separately. Finally, a principal component analysis was conducted to analyse the influence of the soil properties and elevation on the soil variability. It was determined that elevation and clay were the most important contributing properties. Therefore, these can be regarded as key latent variables in this soil. Results showed that low-cost data based on ECa surveys can be used to implement site-specific management in soils with permanent pastures, such as those in the montado or dehesa ecosystems, in the southwest of the Iberian Peninsula.
机译:通常,用于牲畜生产的土壤具有与农业或森林使用类似的高空间变异性。因此,有必要确定主要土壤属性的空间模式作为实现特定现场管理的第一阶段。然而,这必须使用廉价的技术进行,因为这些类型的农场的盈利能力非常低,因此业主需要一个廉价,有效,可靠的方法来了解哪个区域具有类似的生产潜力。使用在许多位置的接触传感器中获得的土壤表观电导率(ECA)测量,作为执行定向土壤采样的基础,在2.3中以两个深度(0-0.25米和0.25-0.50m)拍摄10个样品在埃沃纳(南部葡萄牙)的哈领域。首先,使用回归分析分析ECA与许多土壤性质之间的关系。六种土壤性质(粘土,淤泥,细砂,土壤水分含量,pH和阳离子交换能力明显相关。因此,使用地图代数技术可视化这些变量的空间分布。稍后,利用模糊聚类算法来描绘管理区域,导致两个子字段进行单独管理。最后,进行了主要成分分析,以分析土壤性质的影响和对土壤变异性的影响。确定升高和粘土是最重要的贡献性质。因此,这些可以被视为这种土壤中的关键潜变量。结果表明,基于ECA调查的低成本数据可用于在伊比利亚半岛西南部的永久牧场,例如蒙特多或杜鹃生态系统中的土壤中实现现场专用管理。

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