Fertilizer Estimation using Deep Learning Approach

Abstract

Indian economy is dependent on agriculture and allied activities. The Percentage of population directly or indirectly involved in agricultural actives is more. Due to increase in population and demand for food supply, a large quantity on fertilizers are used in soil, which may result in soil pollution and also degradation of soil quality which may lead to multiple problems for future generations. It is essential to analysis the amount of fertilizers required for a particular crop with respect to the fertility of the soil. Traditionally soil testing is carried out in laboratory and the quantity of fertilizers are recommended by soil science department, but the process takes longer period of time and many farmers do not adopt this method. So it is essential to overcome the problem using advanced technology. The gap between technology and farmers should be bridged.A recommendation system is proposedto predict the amount of fertilizers for a particular crop banana and regression methods for upcoming plantations using Neural Networks . The major soil nutrient are Nitrogen (N), phosphors(p), and potassium (k) plays the major role in crop growth. By default soil contains particular amount of NPK, it varies from place to place. The requirements for each crop also vary. In this paper, a model is structured to recommend the amount of fertilizers required for the crop banana.