Computer vision models enable mixed linear modeling to predict arbuscular mycorrhizal fungal colonization using fungal morphology

Zhang, Shufan; Wu, Yue; Skaro, Michael; Cheong, Jia-Hwei; Bouffier-Landrum, Amanda; Torrres, Isaac; Guo, Yinping; Stupp, Lauren; Lincoln, Brooke; Prestel, Anna; Felt, Camryn; Spann, Sedona; Mandal, Abhyuday; Johnson, Nancy; Arnold, Jonathan

doi:10.1038/s41598-024-61181-5

Title: Computer vision models enable mixed linear modeling to predict arbuscular mycorrhizal fungal colonization using fungal morphology

Journal Article · 12 May 2024 · Scientific Reports

DOI: https://doi.org/10.1038/s41598-024-61181-5 · OSTI ID:2349570

Zhang, Shufan; Wu, Yue; Skaro, Michael; Cheong, Jia-Hwei; Bouffier-Landrum, Amanda; Torrres, Isaac; Guo, Yinping; Stupp, Lauren; Lincoln, Brooke; Prestel, Anna; Felt, Camryn; Spann, Sedona; Mandal, Abhyuday; Johnson, Nancy; Arnold, Jonathan

Abstract The presence of Arbuscular Mycorrhizal Fungi (AMF) in vascular land plant roots is one of the most ancient of symbioses supporting nitrogen and phosphorus exchange for photosynthetically derived carbon. Here we provide a multi-scale modeling approach to predict AMF colonization of a worldwide crop from a Recombinant Inbred Line (RIL) population derived from Sorghum bicolor and S. propinquum . The high-throughput phenotyping methods of fungal structures here rely on a Mask Region-based Convolutional Neural Network (Mask R-CNN) in computer vision for pixel-wise fungal structure segmentations and mixed linear models to explore the relations of AMF colonization, root niche, and fungal structure allocation. Models proposed capture over 95% of the variation in AMF colonization as a function of root niche and relative abundance of fungal structures in each plant. Arbuscule allocation is a significant predictor of AMF colonization among sibling plants. Arbuscules and extraradical hyphae implicated in nutrient exchange predict highest AMF colonization in the top root section. Our work demonstrates that deep learning can be used by the community for the high-throughput phenotyping of AMF in plant roots. Mixed linear modeling provides a framework for testing hypotheses about AMF colonization phenotypes as a function of root niche and fungal structure allocations.

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Sponsoring Organization:: USDOE

Grant/Contract Number:: SC0021386

OSTI ID:: 2349570

Alternate ID(s):: OSTI ID: 2472260

Journal Information:: Scientific Reports, Journal Name: Scientific Reports Journal Issue: 1 Vol. 14; ISSN 2045-2322

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United Kingdom

Language:: English

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