Sampling Design of Soil Physical Properties in a Conilon Coffee Field
| Autor: | Ivoney Gontijo, Eduardo Oliveira de Jesus Santos, Fábio Luiz Partelli, Marcelo Barreto da Silva |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
040101 forestry
biology Espirito santo Agroforestry soil sampling Soil Science 04 agricultural and veterinary sciences Agricultural engineering Geostatistics Coffea canephora biology.organism_classification lcsh:S1-972 Field (geography) Sampling design 040103 agronomy & agriculture 0401 agriculture forestry and fisheries geostatistics Spatial variability lcsh:Agriculture (General) Agronomy and Crop Science Mathematics |
| Zdroj: | Revista Brasileira de Ciência do Solo, Vol 41, Iss 0 Revista Brasileira de Ciência do Solo v.41 2017 Revista Brasileira de Ciência do Solo Sociedade Brasileira de Ciência do Solo (SBCS) instacron:SBCS Revista Brasileira de Ciência do Solo, Volume: 41, Article number: e0160426, Published: 27 APR 2017 |
| ISSN: | 0100-0683 |
| DOI: | 10.1590/18069657rbcs20160426 |
| Popis: | Establishing the number of samples required to determine values of soil physical properties ultimately results in optimization of labor and allows better representation of such attributes. The objective of this study was to analyze the spatial variability of soil physical properties in a Conilon coffee field and propose a soil sampling method better attuned to conditions of the management system. The experiment was performed in a Conilon coffee field in Espírito Santo state, Brazil, under a 3.0 × 2.0 × 1.0 m (4,000 plants ha-1) double spacing design. An irregular grid, with dimensions of 107 × 95.7 m and 65 sampling points, was set up. Soil samples were collected from the 0.00-0.20 m depth from each sampling point. Data were analyzed under descriptive statistical and geostatistical methods. Using statistical parameters, the adequate number of samples for analyzing the attributes under study was established, which ranged from 1 to 11 sampling points. With the exception of particle density, all soil physical properties showed a spatial dependence structure best fitted to the spherical model. Establishment of the number of samples and spatial variability for the physical properties of soils may be useful in developing sampling strategies that minimize costs for farmers within a tolerable and predictable level of error. |
| Databáze: | OpenAIRE |
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