<i>Pseudomonas</i> species isolated from tobacco seed promote root growth and reduce lead contents in <i>Nicotiana tobacum</i> K326
Bibliographic record
Abstract
Endophytic bacteria are generally helpful for plant growth and protection. We isolated from tobacco seeds three Pseudomonas strains (K03, Y04, and N05) that could produce siderophores, indole-3-acetic acid, and 1-aminocyclopropane-1-carboxylate deaminase, fix nitrogen, dissolve phosphorus and potassium, and tolerate heavy metals. In pot experiments, the three isolated strains significantly promoted root growth and increased the root enzyme activity in Nicotiana tobacum K326. Furthermore, bacterial inoculations increased the proportion of residual lead (Pb) by 8.36%-51.63% and decreased the total Pb content by 3.28%-6.38% in the contaminated soil during tobacco planting, compared with uninoculated soils. An effective decrease in Pb content was also found in tobacco leaves with bacterial inoculations. K03 inoculation decreased the Pb content in the upper leaves by 49.80%, and Y04 inoculation had the best effect, decreasing the Pb content in the middle leaves by 70.12%. Additionally, soil pH and root activity had significant effects on transformation and translocation of Pb. The study suggested that in response to Pb pollution in soil, a reasonable application of endophytes (e.g., Pseudomonas) might be a promising approach in promoting tobacco growth and reducing Pb content in tobacco, while simultaneously enhancing Pb stabilization in soils.
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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) | 0.000 | 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".