Crop Recommendation System Using ML

Computer Engineering

A predominant role in the economic growth and development of country is played by agriculture. The major serious issues in the crop productivity is that the farmers do not choose the right crop for cultivation. To improve the crop productivity, a crop recommendation system is to develop that uses to provide machine learning technique. Our research goal is to help farmers pick the best crop for their situation environment by predicting which crops fit well with the factors that influence crop growth such as soil pH, soil nutrients, rainfall, Temperature and humidity. The crop recommendation system classifies the input soil dataset into the recommendable the crop type, Kharif and Rabi. Machine Learning algorithms allow choosing the most profitable crop or predicting the yield for a user-selected crop. This paper presents the utilization of machine learning approaches like Random forest and Decision tree to predict which crop is best for which soil type based on the datasets. Machine learning approaches which could solve the mentioned issues and increase the yield.

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