A control system for fine farming of apple trees

Abstract

Apples are susceptible to diseases during growth that can reduce yields and cause economic losses. The common types of diseases of apple leaves are mainly spotted leaf drop, brown spot, grey spot, tobacco leaf blossom and rust. In this paper, a control system for the fine breeding of apple trees is designed to address the problem of the five diseases mentioned above affecting the growth of apple trees. The system uses a convolutional neural network to build a CNN model for disease identification of apple leaves. The data set is first processed using a pre-processing model (Xception) and the processed data is loaded into the built model. The experiments show that the accuracy of disease recognition using this model is high, and that fine farming of apple trees can be achieved through the control system.