The root system is crucial for plants to absorb water and nutrients, with in situ root research providing insights into root phenotypes and dynamics. While deep-learning-based root segmentation methods have advanced the analysis of root systems, they require extensive manually labeled datasets, which are labor-intensive and time-consuming to produce. Current methods of in situ root observation vary in their effectiveness.