Mycom Selection Software -

[ C_hf = \fracN_studies(host, fungus) \cdot w_study + MD_host \cdot w_MDw_study + w_MD ]

where ( N_studies ) is the number of positive citations and ( MD_host ) is the mycorrhizal dependency score (0–1). Fungi with ( C_hf < 0.3 ) are excluded. User-input soil data (pH, %OM, P-availability) is compared against each fungus’s tolerance range. For each environmental variable ( e ), a membership function ( \mu_e ) is defined: mycom selection software

where ( d_ij ) is the Euclidean distance between trait vectors ( T_i ) and ( T_j ), and ( k = |S| ). The final score for a consortium is: [ C_hf = \fracN_studies(host, fungus) \cdot w_study +

Author: [Author Name(s)] Affiliation: [Institution/Department] Date: April 17, 2026 Abstract The selection of appropriate mycorrhizal inoculants for agricultural crops remains a trial-and-error process, often leading to suboptimal plant-fungal symbiosis. This paper presents MyCoM (Mycorrhizal Community Management) , a novel selection software that integrates phylogenetic trait matching, soil physicochemical data, and crop phenology to recommend optimal arbuscular mycorrhizal fungi (AMF) consortia. The software employs a weighted decision matrix based on three core modules: a host preference database, an environmental tolerance engine, and a functional trait optimizer. Validation against 12 controlled field trials shows that MyCoM-selected consortia increase root colonization rates by an average of 34% and phosphorus uptake efficiency by 27% compared to commercial generalist inoculants. This paper details the software’s architecture, algorithmic logic, user interface, and performance benchmarks. For each environmental variable ( e ), a

The authors declare no competing financial interests. The software is distributed under an MIT license.