Image-based approach for fungal network analysis: reconstructing connectivity with occluded information-Reference-Cited by-同舟云学术

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Image-based approach for fungal network analysis: reconstructing connectivity with occluded information

Published:2023-11-06 Issue: Volume: Page:176-181
ISSN:
Container-title:2023 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)
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Author:

Sten Oscar¹,Dottore Emanuela Del²,Pugno Nicola³,Mazzolai Barbara¹

Affiliation:

1. Istituto Italiano di Tecnologia,Bioinspired Soft Robotics lab,Genova,Italy

2. Istituto Italiano di Tecnologia,Bioinspired Soft Robotics Laboratory,Genova,Italy

3. University of Trento,Laboratory for Bioinspired, Bionic, Nano, Meta Materials and Mechanics,Department of Civil, Environmental and Mechanical Engineering,Trento,Italy

Funder

European Research Council

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10424027/10424015/10424328.pdf?arnumber=10424328

Reference25 articles.

1. Mycorrhizal networks: Mechanisms, ecology and modelling

2. Plant–Plant Communication Through Common Mycorrhizal Networks

3. Underground allies: How and why do mycelial networks help plants defend themselves?

4. Can common mycorrhizal fungal networks be managed to enhance ecosystem functionality?

5. Mechanisms underlying beneficial plant–fungus interactions in mycorrhizal symbiosis

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