Soil productivity analysis based on a fuzzy logic system

Area of Science:

• Agricultural Science
• Soil Science
• Environmental Science

Background:

• Sustainable agriculture relies on maintaining soil productivity.
• Current tools for measuring soil productivity changes are limited.
• Fuzzy logic-based analysis presents a novel approach for soil productivity evaluation.

Purpose of the Study:

• To introduce and apply a fuzzy logic-based system for evaluating soil productivity.
• To decipher soil productivity profiles in the Kocaeli region, Turkey.
• To demonstrate the utility of fuzzy logic in assessing soil quality parameters.

Main Methods:

• Fuzzy logic system developed using pH, salinity, carbonate, and organic matter as input variables.
• Membership functions and rules were established for input and output variables.
• The system was applied to soil samples from the Kocaeli region to determine fuzzy soil productivity values.

Main Results:

• Soil productivity values ranged from 16.9% to 18.1%.
• Organic matter levels were below 30 g kg⁻¹, varying between 22 and 28 g kg⁻¹.
• Lime content ranged from 33-88 g kg⁻¹, and average salt values were between 0.58-0.77 g kg⁻¹.

Conclusions:

• Fuzzy logic analysis successfully deciphered soil productivity profiles in the Kocaeli region.
• The study highlights the potential of fuzzy logic as a tool for assessing soil productivity.
• Findings provide insights into the soil characteristics influencing productivity in the study area.