Abstract
In the study of spatial variability of soil attributes, it is essential to define a sampling plan with adequate sample size. This study aimed to evaluate, through simulated data, the influence of parameters of the geostatistical model and sampling configuration on the optimization process, and resize and reduce the sample size of a sampling configuration of a commercial area composed of 102 points. For this, an optimization process called genetic algorithm (GA) was used to optimize the efficiency of the geostatistical model estimation based on the Fisher information matrix. The simulated data evidenced that the variation of the nugget effect or practical range did not significantly alter the sample size. GA was efficient in reducing the sample size, determining for soil chemical attributes a sample size between 30 and 40 points (29.41 to 39.22% of the initial sampling grid). The presence of spatial dependence was observed for all soil chemical attributes in the two sampling configurations (initial and optimized). The optimized sampling configuration evidenced an increase in trend intensity in the north direction and a more efficient estimation of parameters of the linear spatial regression model.
Highlights
Soil quality is essential to sustainable development and preservation of ecosystems and biodiversity, and the variability of soil chemical attributes is influenced by differences in interactions between soil formation factors and processes, which contribute to the existence of spatial variability of crops (Artur et al, 2014)
All the simulations presented a low variability of the estimated values of V (θ), which means that the optimization process determined a reduced size sample configuration with a higher minimization of V (θ), showing the efficiency of the process
One sample at every 4 or 6 hectares would be required for the composition of the sampling configuration. These conclusions were obtained from an optimization process that considers previously known information, such as an initial sampling configuration and spatial dependence structure of the already estimated attributes
Summary
Soil quality is essential to sustainable development and preservation of ecosystems and biodiversity, and the variability of soil chemical attributes is influenced by differences in interactions between soil formation factors and processes, which contribute to the existence of spatial variability of crops (Artur et al, 2014). It is important for the cultivation system to reduce costs of applying inputs and possibilities of environmental problems in order to improve the management of the production process and maximize the profitability of production (Bernardi et al, 2014). In contrast to traditional samplings that use a fixed number of samples, there is the sequential sampling in which the sample size increases item by item until it reaches a conclusion in order to accept or reject a hypothesis (Santos et al, 2017)
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