Abstract
The soil is composed of several nutrients which are important for the effective growth of plants. Nitrogen, phosphorus, and potassium are micronutrients which are very important for plant growth. There have been several methods and soil tests developed to test the compositions of these nutrients in the soil. Interpreting the results gotten from such tests has been a herculean task for farmers. Employing the use of a soft computing method to interpret such result would be a noble idea. In this paper, we describe the use of fuzzy logic to interpret the values of nitrogen, phosphorus, and potassium (NPK) gotten from conventional soil test to know their levels in the soil and predict possible NPK inputs.
Highlights
Agriculture is a major sector in the Nigerian economy [1]
The government is trying to diversifying the economy back to agriculture because in the past years attention has only been focusing on petroleum
This paper has shown how fuzzy logic as an expert system can be applied to the forecasting of soil fertility
Summary
Agriculture is a major sector in the Nigerian economy [1]. It accounts for the employment of up to 70% of Nigeria’s population. It is necessary to know the constituents of the soil and over the years several methods have been developed and are in use to measure the soil constituents such as indicator methods, metal-electrode, glass-electrode methods, and semiconductor sensor methods for measuring soil PH, direct light indicator for measuring light intensity, litmus test, and a test probe to measure soil PH and a dry test to know amount of nutrients in the soil After all this data has been calculated, the farmer still has to decide what this data means, what crops can be planted or what other action can be taken. The rest of the paper is organized as follows: Literature Review is presented in Section 2 and Methodology is presented in Section 3 while System Implementation is presented in Section 4, and Section 5 comprises Conclusion
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