Study of Agricultural Analysis of Soil using Random Forest Classification in Tirunelveli District

IJEP 42(1): 52-58 : Vol. 42 Issue. 1 (January 2022)

K. Karthigadevi1* and G. Srinivasagan2

 1. Kalasalingam Academy of Research and Education, Department of Computer Applications, Krishnankoil – 626 126, Tamil Nadu, India
2. Rajapalayam Rajus College, Department of Chemistry, Rajapalayam – 626 117, Tamil Nadu, India


In India, there are most of the people get their incomes through agriculture. Plants require various mineral elements for their normal growth and development. The most important elements needed are C, H, O, N, P, K, Ca, Mn, Zn, Mo and Cl. These elements are very essential for plants’ growth. Currently there are lot of mobile applications, software and technologies available in agriculture to get rapid information. But the lack of awareness about these kinds of technologies the farmers suffer a lot and still they are applying traditional methods in agriculture. Nowadays use of natural and chemical fertilizers on crops are the important issues in agriculture. The farmers find it hard to identify the deficiencies in the soil, pH value, EC, soil type and soil texture, choose the correct crops to increase the production. This paper, uses random forest classification algorithm to identify the soil fertility and crop selection in Tirunelveli district. Compared to existing methods, the proposed experimental results show that the random forest classification algorithm for agricultural data analysis produces high accuracy and less processing time.


Attribute selection, Agriculture, Essential nutrient, Soil fertility, Random forest method


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