Abstract: As an organ that extracts water and nutrients from the soil, the root system is vital for a rice plant. Establishing a 3D model to visualize the system structure can materially help the studies on the morphology and functional traits of the roots. Recent advancements in the computerized and non-invasive technologies make the information digitization for scientific research increasingly accessible and significant progresses possible. For instance, utilizing hand drawings and computer tomography (CT), mathematical models were built to vividly simulate the configuration of unearthed root system. Since data acquisition that proceeds model building is essential for an accurate and reliable representation, this article compares and analyzes the principles and characteristics of two classes of detection methods for information collection on the root systems. These methods can be either destructive or in-situ in applications depending upon whether or not the original growth environment was interrupted or destroyed. The 3D modeling and visualization of rice root system is explained in this article from the aspects of manual observation and measurement, machinery vision, 3D digitization by optical instruments, and tomography, etc. The mainstream reconstruction technologies are classified, compared, and analyzed with respect to the pros and cons on the resulting effect as well as the cost and ease of operation. Since environmental conditions are ever-changing, the development of a root system is invariably complex and varied. The affecting factors include the firmness, moisture content, and nutrients distribution of the soil a plant grows on. In addition, the non-transparency and instability of soil has so far hindered the related studies and confined to the fundamental and non-environmental elements, such as, depth of layer and time, for statistical analysis. Consequently, few reports dealt with the dynamic interactions among the multi-environmental factors that effect on the root development are available. Evidently, in the foreseeable future, the newly developed modeling and visualization technologies would usher in innovative applications and deep understanding in the field of study.