Nitrogen- and phosphorus-starved Triticum aestivum show distinct belowground microbiome profiles
Bibliographic record
Abstract
Many plants have natural partnerships with microbes that can boost their nitrogen (N) and/or phosphorus (P) acquisition. To assess whether wheat may have undiscovered associations of these types, we tested if N/P-starved Triticum aestivum show microbiome profiles that are simultaneously different from those of N/P-amended plants and those of their own bulk soils. The bacterial and fungal communities of root, rhizosphere, and bulk soil samples from the Historical Dryland Plots (Lethbridge, Canada), which hold T. aestivum that is grown both under N/P fertilization and in conditions of extreme N/P-starvation, were taxonomically described and compared (bacterial 16S rRNA genes and fungal Internal Transcribed Spacers-ITS). As the list may include novel N- and/or P-providing wheat partners, we then identified all the operational taxonomic units (OTUs) that were proportionally enriched in one or more of the nutrient starvation- and plant-specific communities. These analyses revealed: a) distinct N-starvation root and rhizosphere bacterial communities that were proportionally enriched, among others, in OTUs belonging to families Enterobacteriaceae, Chitinophagaceae, Comamonadaceae, Caulobacteraceae, Cytophagaceae, Streptomycetaceae, b) distinct N-starvation root fungal communities that were proportionally enriched in OTUs belonging to taxa Lulworthia, Sordariomycetes, Apodus, Conocybe, Ascomycota, Crocicreas, c) a distinct P-starvation rhizosphere bacterial community that was proportionally enriched in an OTU belonging to genus Agrobacterium, and d) a distinct P-starvation root fungal community that was proportionally enriched in OTUs belonging to genera Parastagonospora and Phaeosphaeriopsis. Our study might have exposed wheat-microbe connections that can form the basis of novel complementary yield-boosting tools.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".