Research on the detection method of phenotypic information of Pinus massoniana Lamb. seedling root system.

Pinus massoniana (Lamb.) safeguards China's forestry carbon sequestration value and plays a crucial role in achieving dual-carbon goals. The phenotypic information of the root system is a critical criterion for assessing the quality of robust seedlings. To address the issues of high measurement errors, low efficiency in traditional manual root measurement, and the inadequacy of existing 3D reconstruction equipment in evaluating fine root systems, a low-cost and efficient research approach for root system phenotypic information detection was designed. In this study, we outlined the root system phenotypic parameter detection methods and proposed a two-dimensional image-based data collection system. We employed suitable preprocessing methods to effectively eliminate image noise and intuitively capture the root system's skeletal features. Through conditional judgments, we pinpointed the root tip endpoints and main lateral root junctions of the root system's skeleton. The PPSA algorithm was utilized to achieve precise segmentation of main and lateral roots, and mathematical relationships were established between calibrated objects and the real environment to extract root system phenotypic parameters. The results demonstrated that the two-dimensional image-based approach for root system phenotypic information research fulfilled the rapid and efficient quality assessment requirements of nursery seedlings in forest management. [ABSTRACT FROM AUTHOR]