Endophytic rhizobia in barley, wheat and canola roots
Bibliographic record
Abstract
Endophytic rhizobia have been shown to improve the nutrition of nonlegume crops. The objective of this work was to investigate the effects of field pea (Pisum sativum)-based crop rotations on endophytic rhizobia in roots of cereal and oilseed crops. Barley (Hordeum vulgare), wheat (Triticum aestivum) and canola (Brassica rapa) were each grown (a) following inoculated peas, (b) following uninoculated peas or (c) in monoculture. At flag-leaf or flowering growth stage, populations of endophytic rhizobia were usually in the order: crop following uninoculated peas (up to 7244 cells g-1 root DM) > crop following inoculated peas (up to 1660 cells g-1 root DM) > crop grown in monoculture (< 10 cells g-1 root DM). At one of three sites, there were significant positive correlations between endophytic rhizobia and crop N and yield. Populations of rhizobia in bulk soil, rhizosphere, or rhizoplane of nonlegume roots were greater where nonlegume crops were preceded by peas (inoculated or uninoculated) than where they were grown in monoculture. Significant positive correlations between populations of these rhizobia outside roots and crop N or yields were observed at each site. Key words: Crop rotation, inoculation, nitrogen fixation, plant growth-promoting rhizobacteria (PGPR), rhizosphere
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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".