摘要：Core Ideas Three‐dimensional X‐ray imaging is a valuable tool for vadose zone research. Quantitative 3‐D X‐ray image analyses require a large amount of time and expertise. SoilJ is an X‐ray image processing tool for the automatized analyses of X‐ray images. SoilJ lowers the amount of time and expertise needed to evaluate 3‐D X‐ray images. Noninvasive three‐ and four‐dimensional X‐ray imaging approaches have proved to be valuable analysis tools for vadose zone research. One of the main bottlenecks for applying X‐ray imaging to data sets with a large number of soil samples is the relatively large amount of time and expertise needed to extract quantitative data from the respective images. SoilJ is a plugin for the free and open imaging software ImageJ that aims at automating the corresponding processing steps for cylindrical soil columns. It includes modules for automatic column outline recognition, correction of image intensity bias, image segmentation, extraction of particulate organic matter and roots, soil surface topography detection, as well as morphology and percolation analyses. In this study, the functionality and precision of some key SoilJ features were demonstrated on five different image data sets of soils. SoilJ has proved to be useful for strongly decreasing the amount of time required for image processing of large image data sets. At the same time, it allows researchers with little experience in image processing to make use of X‐ray imaging methods. The SoilJ source code is freely available and may be modified and extended at will by its users. It is intended to stimulate further community‐driven development of this software.
