Contrasting Nitrogen Fertilization and<i>Brassica napus</i>(Canola) Variety Development Impact Recruitment of the Root-Associated Microbiome
Bibliographic record
Abstract
Canola ( Brassica napus) is an important broadacre crop, produced under high nitrogen (N) fertilizer application. Modern canola varieties are developed under high N rates but the impacts on root-associated microbiomes of different varieties are unknown. We studied eight canola varieties spanning historical Canadian spring canola development at two sites under high and low N fertility and characterized bacterial and fungal microbiomes in the root and rhizosphere using amplicon sequencing. Environmental conditions and the resulting canola varietal responses strongly affected the root-associated bacterial and fungal microbiomes. Microbes regulated by N fertility in each canola variety were mainly Gammaproteobacteria, Bacteroidia, Actinobacteria, Sordariomycetes, Dothideomycetes, and Agaricomycetes classes. Differentially abundant (DA) microbial taxa showed that N more strongly enriched bacteria in the roots and fungi in the rhizosphere. Each variety had its specific pattern of DA amplicon sequence variants (ASVs) responding to soil N availability, and the profile of DA-ASVs in paired canola varieties were also altered by soil N availability, especially bacteria in the rhizosphere. The yield was strongly associated with a subset of microbial taxa, mainly from Proteobacteria, Actinobacteriota, and Ascomycota. These variety-dependent responses to N and links to yield performance make the root-associated microbiome a promising target for improving the agronomic performance of canola by manipulating microorganisms tailored to soil fertility and plant genotype.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".