Abstract: As an advanced non-invasive imaging technology, CT technology combines X-ray and computer reconstruction algorithms, which can accurately reveal the internal structure of objects. It has great application prospects in the field of agricultural engineering research and has gradually become one of the important technologies to promote the intelligence and precision of agricultural engineering. In order to systematically summarize the application status of CT technology in the field of agricultural engineering and analyze the future development trend of this technology, this paper summarizes the basic principles of CT technology, including equipment structure, workflow, image reconstruction post-processing technology, etc. By comparing with other non-destructive testing technologies, the significant advantages of CT technology in high resolution and strong penetration are highlighted. This paper reviews the application examples of CT technology in many fields of agricultural engineering research. For example, in the quality detection of fruits and vegetables, CT technology can non-destructively detect internal defects of fruits and vegetables, such as internal browning, voids, fibrous tissue, etc., and perform quality classification, which improves the detection efficiency and accuracy. In terms of grain evaluation, CT technology can accurately measure key parameters such as grain size, shape, internal tissue structure, and density, which can be used to evaluate grain quality and predict yield, and provide a scientific basis for breeding and planting management. In terms of stem analysis, CT technology can reveal the microstructure and physiological characteristics of stems, and provide a new perspective for studying the growth and development, lodging resistance, and mechanical strength of stems. In terms of root analysis, CT technology can track the growth process of roots, analyze the effects of roots on soil structure, porosity, and water transport, and provide important data for studying plant-soil interaction and improving soil management. In terms of soil pore analysis, CT technology can obtain three-dimensional pore structure images of soil, and analyze the geometric characteristics and spatial distribution of pores, which can be used to study the permeability, water retention, and permeability of soil, and provide scientific guidance for soil improvement and management. However, the application of CT technology still faces the problems of complex equipment operation processes, high image processing difficulty, detection resolution limitation, high equipment cost, and radiation safety. The operation process of CT equipment is relatively complex, involving multiple steps such as scanning parameter setting, image reconstruction, and post-processing. Moreover, image processing relies on professional software and algorithms, which requires a high technical level and professional knowledge of operators. The resolution of CT equipment has limitations in the application of small-volume agricultural product detection. The high cost of CT equipment and the radiation risk of X-rays to the human body have certain requirements for the installation and use environment, which limits its application in the field of agricultural engineering. In view of the above problems, this paper puts forward the development trend of CT technology applications, including enriching research objects, enhancing application effects, and optimizing technical links. CT technology is applied to the fields of agricultural machinery design, intelligent agricultural platforms, and agricultural education to develop new application scenarios. The development of multimodal imaging technology and low-dose imaging technology improves the level of intelligence and combines with artificial intelligence algorithms such as deep learning to achieve automatic image analysis. The purpose of this paper is to provide a reference for the further application and development of CT technology in the field of agricultural engineering, so as to promote the deep integration of CT technology and agricultural engineering research and its application in related research.