The grading judgment for apples is related to a variety of factors including, size, shape, color, texture, and scars. Traditional manual sorting methods are time consuming and labor intensive. In addition, the accuracy of the method is easily subjective, not repeatable, error-prone, and affected by the sorting environment. This paper presents a complete and automated grading system for apples. The system uses a single-chip microcomputer as the controller of the system, and a PC as the graphics processing unit. It also includes a conveyor, drive motor, frequency converter for motor control, photoelectric sensors, air compressor, and air jets for ejecting the graded apples. The classification algorithm is implemented by using a convolutional neural network (CNN). In order to eliminate contact damage of apples, the system specifically uses air jets as actuators to eject the graded apples into the corresponding bins. At the same time, in order to ensure that an apple triggers the correct ejecting actuator, this paper designs a jet controller with proper logic.