Data_Sheet_1_TAIM: Tool for Analyzing Root Images to Calculate the Infection Rate of Arbuscular Mycorrhizal Fungi.pdf

Arbuscular mycorrhizal fungi (AMF) infect plant roots and are hypothesized to improve plant growth. Recently, AMF is now available for axenic culture. Therefore, AMF is expected to be used as a microbial fertilizer. To evaluate the usefulness of AMF as a microbial fertilizer, we need to investigate the relationship between the degree of root colonization of AMF and plant growth. The method popularly used for calculation of the degree of root colonization, termed the magnified intersections method, is performed manually and is too labor-intensive to enable an extensive survey to be undertaken. Therefore, we automated the magnified intersections method by developing an application named “Tool for Analyzing root images to calculate the Infection rate of arbuscular Mycorrhizal fungi: TAIM.” TAIM is a web-based application that calculates the degree of AMF colonization from images using automated computer vision and pattern recognition techniques. Experimental results showed that TAIM correctly detected sampling areas for calculation of the degree of infection and classified the sampling areas with 87.4% accuracy. TAIM is publicly accessible at http://taim.imlab.jp/.

丛枝菌根真菌（Arbuscular mycorrhizal fungi，简称AMF）感染植物根系，并被假设能够促进植物生长。近期，AMF已可实现无性系培养。因此，AMF有望被用作微生物肥料。为了评估AMF作为微生物肥料的有用性，我们需要研究AMF根系侵染程度与植物生长之间的关系。计算根系侵染程度的常用方法称为放大交点法，该法需人工操作，劳动强度大，难以开展广泛调查。因此，我们通过开发名为“分析根系图像以计算丛枝菌根真菌侵染率的工具：TAIM”的应用程序，实现了放大交点法的自动化。TAIM是一款基于网络的程序，它利用自动化计算机视觉和模式识别技术，从图像中计算AMF的侵染程度。实验结果表明，TAIM能够正确检测用于计算侵染程度的采样区域，并以87.4%的准确率对采样区域进行分类。TAIM可通过http://taim.imlab.jp/公开访问。