Spatial variability of the chemical, physical and biological properties in lowland cultivated with irrigated rice

Revista Brasileira de Ciência do Solo

José Maria Barbat Parfitt²  Luís Carlos Timm¹  Eloy Antonio Pauletto¹  Rogério Oliveira De Sousa¹  Danilo Dufech Castilhos¹  Conceição Lagos De Ávila¹  Nestor Luis Reckziegel¹ 

[1] ,EmbrapaPelotas RS

关键词: geostatistics;    soil sampling;    spatial dependence;    geoestatística;    várzea;    amostragem do solo;    dependência espacial;   

DOI  :  10.1590/S0100-06832009000400007

来源: SciELO

【 摘 要 】

In the areas where irrigated rice is grown in the south of Brazil, few studies have been carried out to investigate the spatial variability structure of soil properties and to establish new forms of soil management as well as determine soil corrective and fertilizer applications. In this sense, this study had the objective of evaluating the spatial variability of chemical, physical and biological soil properties in a lowland area under irrigated rice cultivation in the conventional till system. For this purpose, a 10 x 10 m grid of 100 points was established, in an experimental field of the Embrapa Clima Temperado, in the County of Capão do Leão, State of Rio Grande do Sul. The spatial variability structure was evaluated by geostatistical tools and the number of subsamples required to represent each soil property in future studies was calculated using classical statistics. Results showed that the spatial variability structure of sand, silt, SMP index, cation exchange capacity (pH 7.0), Al3+ and total N properties could be detected by geostatistical analysis. A pure nugget effect was observed for the nutrients K, S and B, as well as macroporosity, mean weighted diameter of aggregates, and soil water storage. The cross validation procedure, based on linear regression and the determination coefficient, was more efficient to evaluate the quality of the adjusted mathematical model than the degree of spatial dependence. It was also concluded that the combination of classical with geostatistics can in many cases simplify the soil sampling process without losing information quality.

【 授权许可】

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