Evaluation of Agricultural Soil Resources Using Fuzzy Modeling

Assessment of agricultural soil resources is a very difficult because exists knowledge is much fuzzy. Developed fuzzy model is effective tool for dealing with randomness and uncertainties. This model is based on a two-level system of fuzzy indicators. The first level is individual fuzzy indicators (IFI), reflecting the assessment of individual characteristics. Second level is combined fuzzy indicators (CFI), reflecting a combination of individual indicators. IFI are developed for the four characteristics of the soil (humus, amount absorbed cations, acidity (pH) and physical clay content). The proposed method is illustrated with a simple example.


Introduction
The ultimate goal of sustainable agriculture is to develop farming systems that are productive and profitable, conserve the natural resource base, protect the environment, and enhance health and safety over the long term.Assessment of agricultural soil resources is a very important component of understanding agriculture potential and therefore maintaining a sustainable agriculture.Many investigations have been carried out with aims to inventory and protect agricultural soil resources (Behzad, 2009;Dorronsoro, 1998;FAO, 1983FAO, , 1984FAO, , 1985;;Teka & Haftu, 2012;Rossiter, 1994).Research on classification of agricultural soil types based on their ability to sustain agricultural crops (CDC, 2003) and assessment of soil capability for agriculture (Ali et al., 2007) are well known.Recently many methods and tools have been developed to evaluate agricultural soil resources.These tools have incorporated state of the art of knowledge in agronomy, soil science, and economics.Crop simulation models, for example, are excellent tools for assessing potential impacts of weather-related production variability associated with natural resources (Ascough et al., 2005).
The process of assessing agricultural soil resources is full of uncertainty.Uncertainty is inherent in this process because it involves both data and model imprecision.This uncertainty ranges from measurement error, to inherent variability, to instability, to conceptual ambiguity, to over-abstraction, or to simple ignorance of important factors.Current technology utilized in assessment tools do not necessarily deal well with this uncertainty because they depend on the multiplicity of specific relationship of the measured components.In other words, small errors in any measured data or modeled relationship can propagate through the tool, potentially resulting in large errors in interpretation.
For dealing with the uncertainties and randomness that occurs with assessing agricultural land, fuzzy sets theory and fuzzy logic can be utilized (Jager, 1995;Pedrycz & Gomide, 1998).Fuzzy set theory is a mathematical approach that has been used successfully to address many scientific and technical problems dealing with abstract questions.
Application of fuzzy modeling for evaluation of agricultural soil resources was discussed in Torbert et al. (2009Torbert et al. ( , 2010)).This article uses fuzzy modeling for the evaluation of agricultural soil resources.
The article is organized into two parts.The first part addresses the use of fuzzy indicator modeling for the evaluation of agricultural soil resource, and the second part contains an example which illustrates this approach. www.ccsen

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Model
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Exampl
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Table 4
Assessment of agricultural soil resources is a very difficult because exists knowledge is much fuzzy.Developed fuzzy model is effective tool for dealing with randomness and uncertainties.This model is supplied by computer program.To illustrate the proposed method, a series of calculations were made.

Table 5 .
Results of complete assessment of soil resources