Colonization and growth promotion of outplanted spruce seedlings pre-inoculated with plant growth-promoting rhizobacteria in the greenhouse
Bibliographic record
Abstract
Seeds of two hybrid spruce (Picea glauca (Moench) Voss × Picea engelmannii Parry ex Engelm.) ecotypes were inoculated with one of six plant growth-promoting rhizobacteria (PGPR) strains previously shown to be able to stimulate spruce growth in controlled environments. The resulting seedlings were grown in the greenhouse for 17 weeks before outplanting at four reforestation sites. Inoculation with five of the six strains caused significant seedling growth promotion in the greenhouse, which necessitated analysis of relative growth rates (RGR) to evaluate seedling performance in the field. Four months after outplanting, most strains enhanced spruce shoot or root RGRs in the field, but seedling growth responses were strain specific. For example, Pseudomonas strain Ss2-RN significantly increased both shoot and root RGRs by 10-234% at all sites, but increases of 28-70% were most common. In contrast, Bacillus strain S20-R was ineffective at all outplanting sites. In addition, seedlings inoculated with four of the six strains had significantly less shoot injury than control seedlings at all sites. Evaluation of root colonization by PGPR indicated that bacterial population declines were not related to spruce growth response variability in the field. Our results indicate that once plant growth promotion is induced in the greenhouse, seedling RGR can increase by more than 100% during the first growing season in the field. However RGR increases of 21-47% were more common and may be more representative of the magnitude of biomass increases that can result from PGPR inoculation.
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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) | 0.001 | 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 | 0.001 |
| 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".