Analysis of the root diameter distribution from time series images of real and simulated Cassava root systems

The data was collected, simulated and analyzed in the framework of the CassavaStore project (a collaboration between IBG-2, Forschungszentrum Jülich, Germany and different institution from Thailand; for details see https://www.international-bioeconomy.org/cassavastore_eng). Aim of this project is to get a better understanding of storage root development in cassava (<em>Manihot esculenta</em> Crantz) in order to optimize cassava growth with respect to variety breeding and growth management. The storage root is one of the main providers of starch in Thailand and therefore of high economic importance. Monitoring the formation of storage roots over time via quantification of the root diameter distribution of excavated root systems was one of the key aspects addressed in this project. To measure the diameters a software was developed that identifies roots in RGB images and analyzes the diameters along each identified root automatically. The published data contains 1) analyzed images from cassava roots that were acquired in a video box; 2) simulated virtual root model images with known root diameter distributions that were used to validate the analysis approach; 3) a description of the data and the folder structure.本数据集的采集、模拟与分析工作依托CassavaStore项目框架开展：该项目由德国于利希研究中心IBG-2与泰国多家机构合作完成，项目详情可参见https://www.international-bioeconomy.org/cassavastore_eng。本项目的核心目标为深入解析木薯（*Manihot esculenta* Crantz）贮藏根的发育机制，以此优化木薯品种选育与种植管理相关的生长调控策略。贮藏根是泰国主要的淀粉供应源之一，因此具备极高的经济价值。通过量化挖掘所得根系的直径分布，动态追踪贮藏根的形成过程，是本项目的核心研究内容之一。为实现根径测量，研究团队开发了一款专用软件，可自动识别RGB图像中的根系，并沿每条识别出的根系自动分析其直径参数。本次公开的数据集包含以下三部分内容：1）在视频采集箱中获取的木薯根系分析图像；2）用于验证该分析方法的、带有已知根径分布的模拟虚拟根系模型图像；3）数据集说明与文件夹结构文档。