Abstract

Soil health plays an important role in agricultural productivity and sustainability. However, traditional soil testing reports generated from a soil testing lab gives a crisp numerical value for parameters such as PH, Phosphorus, Nitrogen, Organic Carbon, Potassium, etc. In real-life applications, these parameters are uncertain or in range due to measurement and environmental variations. This article presents a fuzzy logic-based framework for soil testing methods to predict the soil health condition in linguistic terms such as excellent, good, moderate, and poor, using triangular fuzzy numbers. The ten soil parameters were considered pH, Nitrogen (N), Phosphorus (P), Potassium (K), Organic Carbon (OC), Electrical Conductivity (EC), Zinc (Zn), Iron (Fe), Copper (Cu), and Manganese (Mn). Each parameter is represented into a fuzzy triangular number. A Python program is used to mapped the membership function values into four soil health categories. 

Keywords

Fuzzy logic, Soil Health, Triangular Fuzzy Number, Python, Membership Function, Linguistic Parameters. 

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