Intelligent Seed Selection for Precision Agriculture Using Machine Learning

The agricultural sector continually seeks innovative solutions, and inexperienced farmers do not know how to choose the suitable seed for their agricultural land. This causes unstable crop harvesting and waste of money due to lower crop yields on land because of insufficient knowledge about land type and seed type. To rectify this problem, this research work has proposed a machine learning solution to predict the seed based on the land's atmosphere, such as NPK levels, humidity, pH, temperature, and rainfall. This solution achieves 99.5% accuracy in effectively tackling all these problems faced by inexperienced or young farmers. This research found that the Random Forest Classifier algorithm of machine learning is the best fit for this data. There are 22 types of seeds, including grains, pulses, fruits, and cash crops used for this research.