Application of Machine Learning Models for Crop Recommendation

Abstract

Optimizing agricultural yields is essential for nations whose agricultural industries are strong economic drivers. Farmers could increase their yields if they knew what to plant based on their location. This paper builds a crop recommendation system using machine learning algorithms that can aid farmers’ in increasing crop yield. The proposed system classify soil using a variety of machine learning algorithms, which enables the system to suggest crops to grow based on the characteristics of the specific soil. Only four soil characteristics are considered, potassium, nitrogen, phosphorus, and pH value. Several experiments are conducted in order to select the best machine learning algorithm for crop recommendation. Experimental results show that the proposed system can recommend crop to increase yearly yield efficiently.