Classification of crop based on macronutrients and weather data using machine learning techniques
Ritesh Dash, Dillip Dash, G.C. Biswal
Abstract
Food production in any country depends primarily on the type of soil and the weather condition. Out of the different crop production types in this research, three major crops have been considered, such as rice, wheat, and sugarcane. The crop growth generally depends on the macronutrients and micronutrient content of the soil, which is again a parametric representation of different climatic conditions such as rain, humidity, temperature, sunlight, and pH content of the soil. This research focused on establishing and interrelating the micronutrients and the weather parameters and classifying the type of crop based on the micronutrients using a support vector machine and decision tree algorithm. Different types of tools, such as curve fitting and data analysis using Python-3.9.0, have been used for prediction purposes.