• Soil fungi establish mutualistic interactions with the roots of most vascular land plants. Arbuscular mycorrhizal (AM) fungi are among the most extensively characterised mycobionts to date. Current approaches to quantifying the extent of root colonisation and the abundance of hyphal structures in mutant roots rely on staining and human scoring involving simple yet repetitive tasks which are prone to variation between experimenters.
• We developed Automatic Mycorrhiza Finder (AMFinder) which allows for automatic computer vision-based identification and quantification of AM fungal colonisation and intraradical hyphal structures on ink-stained root images using convolutional neural networks.
• AMFinder delivered high-confidence predictions on image datasets of roots of multiple plant hosts (Nicotiana benthamiana, Medicago truncatula, Lotus japonicus, Oryza sativa) and captured the altered colonisation in ram1-1, str, and smax1 mutants. A streamlined protocol for sample preparation and imaging allowed us to quantify mycobionts from the genera Rhizophagus, Claroideoglomus, Rhizoglomus and Funneliformis via flatbed scanning or digital microscopy, including dynamic increases in colonisation in whole root systems over time.
• AMFinder adapts to a wide array of experimental conditions. It enables accurate, reproducible analyses of plant root systems and will support better documentation of AM fungal colonisation analyses. AMFinder can be accessed at https://github.com/SchornacklabSLCU/amfinder.

中文翻译：

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基于深度学习的植物根系丛枝菌根真菌定量分析

• 土壤真菌与大多数维管陆生植物的根建立互惠相互作用。丛枝菌根 (AM) 真菌是迄今为止特征最广泛的真菌生物之一。目前量化根定植程度和突变根中菌丝结构丰度的方法依赖于染色和人类评分，涉及简单但重复的任务，这些任务容易在实验者之间发生变化。
• 我们开发了自动菌根查找器 (AMFinder)，它允许使用卷积神经网络在墨水染色的根图像上基于计算机视觉自动识别和量化 AM 真菌定植和根内菌丝结构。
• AMFinder 对多种植物宿主（Nicotiana benthamiana、Medicago truncatula、Lotus japonicus、Oryza sativa）的根图像数据集进行了高度可信的预测，并捕获了ram1-1、str和smax1突变体中改变的定殖。用于样品制备和成像的精简协议所允许我们能够量化从属mycobionts Rhizophagus，Claroideoglomus，Rhizoglomus和Funneliformis经由平板式扫描或数字显微镜，包括随着时间的推移动态增加定植在整根系统。
• AMFinder 适用于各种实验条件。它可以对植物根系进行准确、可重复的分析，并将支持更好地记录 AM 真菌定植分析。AMFinder 可在 https://github.com/SchornacklabSLCU/amfinder 访问。