In agronomic problems the sampling procedure may create some confusion and bias in the analysis. Geostatisrics provides a method for the analysis of the spatial and temporal properties in a data set and a method of interpolation between selected points. This paper describes the theory of geostatistics and its application to selected agronomic problems. Geostatistics considers a set of data collected in either space or time at discrete intervals. These samples may be correlated with each other to provide some unique information about the parameters which would not be detected in the classical statistical methods. Through the application of geosraristics to this type of problem, we can estimate the spatial or temporal dependence of samples and from this knowledge arrive at an estimation of the sampling procedures or structure at a field. The application of these techniques is shown for air temperature, surface temperature, yield, clay content, and fertilizer content in various fields and reveals the versatility of the techniques. Geostatistics also allows for the evaluation of the dependence between two parameters in either time or space. From this information it is possible to develop sampling procedures which would allow the more costly or time consuming variable to be sampled less frequently and estimated from the other variable by the method of kriging. This report summarizes all of these techniques and provides several different examples of their utilization. Examples of the computer code are provided for the reader wishing to apply these techniques.

Spatial variability of 1,280 field‐measured infiltration rates on Yolo loam (fine‐silty, mixed, nonacid, thermic Typic Xerorthents) was studied using geostatistical concepts. The measurements were made at the nodes of an irregular grid consisting of 160 rows and eight columns. Sample spacing within columns was 1 m. Columns were spaced irregularly at 1, 5, 15, and 19 m.A variogram for the 1,280 measurements was used to krige 800 additional values within five more columns and to draw a contour map of the area.The large number of measured values made it possible to calculate the minimum number of samples necessary to reproduce the infiltration rate measurements with a fairly large approximation. As a result, it could be concluded that a minimum of 128 samples was enough to obtain nearly the same information as with 1,280 samples. A suggestion on how to use autocorrelograms in sampling schemes is presented.

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RESUMO

O objetivo deste trabalho foi estudar, mediante a geoestatística, a variabilidade espacial de pH, Ca, Mg, P e K em Latossolo Vermelho-Escuro distrófico, textura argilosa, cultivado durante cinco anos consecutivos (1992-1996), em três sistemas de preparo (arado, grade e plantio direto) na Embrapa-Centro Nacional de Pesquisa de Arroz e Feijão, em Santo Antônio de Goiás, GO. Das 30 combinações entre características químicas do solo, profundidades de coleta e sistemas de preparo, 14 apresentaram efeito pepita puro, indicando ausência de dependência espacial. Semivariogramas direcionais revelaram forte e moderada dependência espacial na direção de Y. Experimentos longevos com práticas culturais orientadas em uma única direção tendem a mudar a estrutura espacial das propriedades do solo, o que indica ser a razão dos resultados obtidos. A direção de anisotropia está mais associada com o tratamento arado e a mais forte dependência espacial foi verificada com relação ao pH no sistema de preparo arado na profundidade de 5-20 cm. A localização das amostras para estimar os valores das características químicas do solo deve levar em conta as operações de campo, e cuidados devem ser tomados em relação à amostragem casual.As amostras devem ser retiradas em outras direções, para que uma representação mais realista da área amostrada seja obtida.