Artificial Neural Networks in Agriculture: A Survey

Abstract: In many fields, including agriculture, neural networks have become a very effective method. In this paper, we discuss the applications of neural networks in the field of agriculture, including their advances, specifically in classification, decision-making, pattern recognition, crop yield prediction, plant identification, classification of weed images, remote sensing, identification of plant diseases, precision farming, and agricultural enhancement spatial data analysis. Among these, computer techniques in the field of agriculture are also based on neural networks, especially in the sense of soil and water. The survey was used to convey information about applications, processes, future innovations, and challenges in applying Artificial Neural Network (ANN) techniques in agricultural innovations.

Keywords: Artificial Neural Networks, Agriculture, Soil Classification, Crop Management, Plant Disease