Bacterial Microbiomes Associated with the Rhizosphere, Root Interior, and Aboveground Plant Organs of Wheat and Canola at Different Growth Stages
Bibliographic record
Abstract
Beneficial bacteria associated with agricultural crops may potentially increase crop productivity and health. However, during various plant developmental processes, shifts in the diversity and function of bacterial communities often occur. This study investigated the diversity of bacterial communities associated with the rhizosphere, roots, and aboveground plant organs of wheat and canola at stem elongation, flowering, and ripening stages. The growth-chamber experiment consisted of wheat and canola grown in Orthic Brown Chernozem Calcic Kastanozem and Orthic Black Calcic Chernozem soils from agricultural fields in Saskatchewan, Canada. Rhizosphere bacterial communities of wheat and canola were mainly influenced by soil characteristics, whereas a specific root endophytic community was associated with each crop species. These results suggest that each crop may select distinct root bacterial endophytes from the rhizosphere. Bacteria associated with aboveground plant organs exhibited high variability among crop species and soils. The most abundant bacterial genera associated with the rhizosphere of the crops included Gemmatimonas, Solirubrobacter, and Nocardioides, as well as unclassified genera of families Commamonadaceae, Chitinophagaceae, and Sphingomonadaceae. Other genera (e.g., Stenotrophomonas, Streptomyces, and Variovorax) were predominant in wheat roots, whereas species of Lentzea and Pantoea were the most abundant root endophytes detected in canola. Bacterial communities associated with aboveground organs consisted mostly of species of Corynebacterium and Pseudomonas, and unclassified members of the family Enterobacteriacaeae. This study also revealed that plant growth stages can modulate the diversity of rhizosphere and endophytic bacteria. The influence of plant growth stages on the bacterial microbiome associated with wheat and canola was crop and organ specific.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".