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Comparison of three methods for delineating management zones for site-specific crop management

机译:特定于现场作物管理划定管理区三种方法的比较

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The goal of this study was to evaluate different strategies for defining homogeneous zones, and to verify their usefulness by comparing soil moisture contents and crop yields. Data were obtained from a field experiment near General Pico, La Pampa, Argentina, with a sampling grid of 598 points. Soil texture, organic matter, available phosphorus, pH, and electrical conductivity were determined. Altimetry was obtained by a GPS (Garmin 19X). Corn yields and available soil moisture contents were determined in a 184 point grid. Treatments were early and late planting date, and control and 100 kg N ha(-1). MULTISPATI-PCA was used to carry out for multivariate spatial analyses of soil attributes. The synthetic variables (sPC) were analyzed, mapped and used for determination of homogeneous zones by three strategies: S1-natural rupture method on sPC1, S2-Fuzzy k-means cluster analysis on soil variables and S3-Fuzzy k-means cluster analysis on all sPC. Zones were compared for means of soil variables, available soil water and maize yields. The three tested statistical strategies divided the field in a very similar manner when the minimum number of zones was considered, with coincidence in the classification of 98% of the sampled grid points. The different strategies resulted in different number of zones with different characteristics. The choice of the method depends on the objectives for determination of management zones. In our case, for fertilization management zonification might prioritize the differentiation of OM and available P contents and use S3, while if water was the main limiting factor, the management zones would be two according to S1 or S2, responding to textural and altimetry differences. (C) 2017 Elsevier B.V. All rights reserved.
机译:本研究的目标是评估定义均地区的不同策略,并通过比较土壤水分含量和作物产量来验证其有用性。数据是从阿根廷普通科帕,拉普纳州La Pampa的一般实验中获得的,采样网格为598分。确定土壤纹理,有机物,可用磷,pH和导电率。通过GPS(Garmin 19x)获得的高度偏转。在184点网格中测定玉米产量和可用的土壤水分含量。治疗是早期和晚期种植日,并控制和100kg n ha(-1)。 MultiSpati-PCA用于进行土壤属性的多变量空间分析。分析了合成变量(SPC),映射并用于通过三种策略测定均匀区域:S1-自然破裂方法对SPC1,S2-FIZZY K-MERIAL对土壤变量的集群分析和S3模糊K-MERIAL集群分析所有SPC。比较区域,以土壤变量,可用土壤水和玉米产量进行比较。当考虑最小区域的最小区域时,三种测试的统计策略以非常相似的方式划分了该领域,在分类的98%的采样网格点的分类中巧合。不同的策略导致不同特征不同的区域。该方法的选择取决于确定管理区的目标。在我们的案例中,对于受精管理,Zonification可能优先考虑OM和可用的P内容和使用S3,而如果水是主要限制因素,则管理区域将是根据S1或S2的两个,响应纹理和高度差异。 (c)2017 Elsevier B.v.保留所有权利。

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