Populations and functional diversity of bacteria associated with barley, wheat and canola roots
Bibliographic record
Abstract
We investigated the effects of field pea (Pisum sativum)-based crop rotations on endophytic bacteria in roots and surrounding soil of cereal and oilseed crops. Barley (Hordeum vulgare), wheat (Triticum aestivum) and canola (Brassica rapa) were each grown (a) following peas inoculated with Rhizobium leguminosarum bv. viceae, (b) following uninoculated peas or (c) in monoculture. At flagleaf (cereal) or flowering (canola) growth stage, populations of soil-extract agar (SEA)-culturable bacteria ranged from log10 7.12 to log10 7.82 cells g-1 soil dry weight in the bulk soil, log10 7.15 to log10 8.12 cells g-1 soil in the rhizosphere, log10 7.77 to log10 10.39 cells g-1 root dry matter (DM) on the rhizoplane, and log10 5.56 to log10 7.63 cells g-1 root DM in root interiors (endophytic bacteria). Differences between treatments in populations and functional diversity of bacteria depended on where the bacteria were sampled in the continuum from bulk soil to root interiors. This affected correlations with crop N and yield because these crop parameters were lowest in monoculture. Thus, populations of endophytic bacteria and functional diversity of rhizospheric bacteria were negatively correlated with crop N accumulation and yields. However, the diversities of endophytic and bulk soil bacteria were positively correlated with crop N and yields. Key words: Community-level physiological profile, crop rotation, substrates, endophytic bacteria, microbial functional diversity, 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".