Abundance of the arbuscular mycorrhizal fungal taxa associated with the roots and rhizosphere soil of different durum wheat cultivars in the Canadian prairies
Bibliographic record
Abstract
Understanding the variation in how wheat genotypes shape their arbuscular mycorrhizal (AM) fungal communities in a prairie environment is foundational to breeding for enhanced AM fungi-wheat interactions. The AM fungal communities associated with 32 durum wheat genotypes were described by pyrosequencing of amplicons. The experiment was set up at two locations in the Canadian prairies. The intensively managed site was highly dominated by Funneliformis. Genotype influenced the AM fungal community in the rhizosphere soil, but there was no evidence of a differential genotype effect on the AM fungal community of durum wheat roots. The influence of durum wheat genotype on the AM fungal community of the soil was less important at the intensively managed site. Certain durum wheat genotypes, such as Strongfield, Plenty, and CDC Verona, were associated with high abundance of Paraglomus, and Dominikia was undetected in the rhizosphere of the recent cultivars Enterprise, Eurostar, Commander, and Brigade. Genetic variation in the association of durum wheat with AM fungi suggests the possibility of increasing the sustainability of cropping systems through the use of durum wheat genotypes that select highly effective AM fungal taxa residing in the agricultural soils of the Canadian prairies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".