| Crop | Soil pH | T2 Colonization (%) | T3 Colonization (%) | T4 Colonization (%) | T3 P-uptake vs. T2 | |------|---------|---------------------|---------------------|---------------------|--------------------| | Maize | 6.2 | 42.3 (4.1) | 61.7 (3.8)* | 58.2 (5.2) | +31% | | Soybean| 5.8 | 38.7 (3.5) | 52.4 (4.0)* | 54.1 (3.9) | +26% | | Wheat | 7.4 | 31.2 (2.9) | 48.9 (3.3)* | 47.5 (4.1) | +24% | | Tomato | 6.5 | 45.0 (3.2) | 67.2 (4.4)* | 63.5 (4.8) | +29% |
The authors declare no competing financial interests. The software is distributed under an MIT license. mycom selection software
Mycorrhiza, selection software, agroinformatics, symbiosis optimization, AMF inoculants 1. Introduction Arbuscular mycorrhizal fungi (AMF) form mutualistic associations with over 80% of terrestrial plants, enhancing water and nutrient acquisition in exchange for photosynthetic carbon (Smith & Read, 2008). Despite this potential, commercial mycorrhizal inoculants often fail in the field due to a mismatch between the fungal species selected and the specific crop–soil–climate context (Hart et al., 2018). | Crop | Soil pH | T2 Colonization
[ C_hf = \fracN_studies(host, fungus) \cdot w_study + MD_host \cdot w_MDw_study + w_MD ] [ C_hf = \fracN_studies(host, fungus) \cdot w_study +
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:
[ FD(S) = \frac2k(k-1) \sum_i<j d_ij ]