This paper explores the use of artificial neural networks to reduce fertilizer consumption and increase agricultural output. The two components of the system are the expert knowledge based on the land report that stimulates the potential yield through appropriate organic matter deficient in minerals in the soil. There are eight parallel systems in the system structure. Expert farmer interviews along with professionals in the fields of water, soil, and agronomy formed the basis of the integrated knowledge and formation. Over the course of three years, an extensive daily field measurement program and laboratory analysis were used to assess fertilizer consumption in the agroclimatic zone and calculate the precise amount of fertilizer required for each individual farm. In order to determine whether an artificial neural network may be feasible and produce the desired results for the crops, the aforementioned data was examined using MATLAB.