基于Micro-CT的土壤结构变化三维可视化量化表征方法

Quantitative Characterization of Soil Structural Changes in 3D Visualization Based on Micro-CT

摘要:

机械压实是导致土壤结构和功能改变，进而制约农业可持续发展的重要因素之一。本文采集砂土、壤土和粘土3种不同质地土壤，采用机械加压方式模拟制备了不同压实程度的土壤样品，并使用先进的Skyscan 1275 Micro-CT系统进行样品扫描。比较了主动轮廓（AC）、标记分水岭（MBW）和K-means 3种不同算法对土壤孔隙和团聚体结构样品Micro-CT 图像的分割效果，结果表明K-means图像分割算法最优。采用形态学分水岭算法和Canny 边缘检测算法有效实现了土壤团聚体和孔隙个体的原位分离。基于K-means分割算法，优化提出了一种土壤物理结构Micro-CT原位、三维、可视化量化表征方法，原位三维可视化呈现了不同压实土壤样品孔隙和团聚体结构分布量化信息。Micro-CT成像表征结果与实验室分析结果具有很好的一致性。研究结果为土壤压实以及土壤结构数字化图谱等相关研究提供了快速分析方法。

Abstract:

Mechanical compaction is one of the key factors leading to changes in soil structure and function, thereby constraining the sustainable development of agriculture.Three different types of soil, i.e. sand, loam and clay, were collected. Mechanical compaction was applied to simulate various compaction levels of soil samples, and the samples were subsequently scanned by using an advanced Skyscan 1275 Micro-CT system. The performance of three different algorithms—active contour (AC), marker based watershed (MBW) and K-means—on the segmentation of Micro-CT images of soil pores and aggregate structure was compared and the K-means image segmentation algorithm exhibited the best performance. Furthermore, the morphological watershed algorithm and Canny edge detection algorithm were used to effectively achieve the in-situ separation of individual soil aggregates and pores. Based on the K-means segmentation algorithm, a 3D in-situ visualization approach was established to quantitatively characterize the physical structure of soil using Micro-CT, enabling the visualization of pore and aggregate structures in different compacted soil samples. The Micro-CT imaging results were in excellent agreement with laboratory analyses. These findings can provide a rapid and environmentally friendly analytical tools for evaluating soil compaction and digitally mapping soil structure.