As one of the most important food crops in the world, the quality assurance of corn seeds is of utmost significance in all stages of production, storage, circulation and breeding. However, the traditional detection method has some disadvantages, such as high labor intensity, strong subjectivity, low efficiency, cumbersome operation, high cost and possibly harmful to human health. In view of this, it is of great significance to study more advanced detection methods. In this paper, the application of near infrared spectroscopy and its imaging technology in the quality detection of corn seeds was reviewed. Firstly, the principles of these two technologies were introduced, and their components, data acquisition and processing methods, as well as portability were compared and discussed. Then, the application of these methods to the main quality of corn seeds (including variety and purity, vigor, internal components, mycotoxins and other qualities such as frost damage, hardness and maturity, etc.) was reviewed. The significance of corn quality characteristics and the function of the applied algorithm were emphasized.. Finally, the future research direction of spectral and its imaging technology was proposed, aiming to further enhance the accuracy, reliability, and practicability of the detection technology, provide valuable reference information for researchers, and contribute to global food security and sustainable agricultural development.