Wheat is one of the most important food crops in the world, and its root system serves as a key organ for water and nutrient absorption. Its phenotypic characteristics are of great significance for understanding the growth status of wheat and soil environment. However, the underground growth characteristics of the root system pose challenges for its observation. A wheat aquatic cultivation device, a flexible liquid exchange device based on siphon principle, and a root image acquisition system were developed. An image refraction correction method was developed for the system. Then a three-dimensional point cloud model of the root system was constructed by using SFM algorithm, and relevant surface features were extracted. Experimental results showed that the flexible liquid exchange device increased the similarity of root image structure before and after liquid exchange to 0.98. The refraction correction method reduced image errors by 62%. Furthermore, the proposed device and method were utilized to investigate the influence of nitrogen environment on the growth and development of wheat roots. The research results indicated that under low nitrogen conditions, wheat roots exhibited a deeper and more densely distributed growth trend. In addition, compared with nitrogen efficient varieties, nitrogen inefficient varieties were more sensitive to changes in nitrogen environment. The device and method proposed can contribute to high-throughput three-dimensional phenotype analysis of plant roots, opening up a perspective for root research in the development of smart agriculture driven by big data.