A crop recommendation system to maximize the crop yield using machine learning technique in precision agriculture

Abstract

The essential building block of a developing economy is a promising agricultural system. Besides food and raw materials, agriculture provides employment opportunities for a considerable population. The primary issue faced by farmers is the selection of the right crop based on parameters such as soil nutrients, seasonal weather, etc. Various factors such as climate, soils, market price, government initiatives and producer preferences influence the crop selection. Farmers typically cultivate the crops based on its market price and financial gains rather than considering soil conditions which may lead to undesirable outcomes for the farmers and soil. Precision agriculture is a cutting-edge method that uses research data on soil types, characteristics, and crop yield to recommend the best crop based on site-specific attributes. Cultivating the crop that best fits the soil characteristics is essential to decrease the need for soil treatment, cost and environmental damage. By choosing the appropriate crops for the available soil and environment, yields can be maximized, and irrigation needs can be reduced. newline