A non-K+-solubilizing PGPB (Bacillus megaterium) increased K+ deprivation tolerance in Oryza sativa seedlings by up-regulating root K+ transporters
Bibliographic record
Abstract
Potassium is one of the principal macronutrients required by all plants, but its mobility is restricted between soil compartments. Numerous studies have shown that Plant Growth Promoting Bacteria (PGPB) can facilitate nutrient uptake. The present work examined the effects of the PGPB (Bacillus megaterium) on rice plants subjected to potassium deprivation. To study only direct effects of B. megaterium, we first checked its lack of capacity to solubilize soil K. Rice plants were provided with 1.5 mM K (100%) or 0.015 mM K (1%) and growth related parameters, nutrient concentrations and gene expression of K+ transporters were determined. After two weeks, the 1% K treatment reduced growth of non-inoculated plants by about 50% compared with the 100% K treatment. However, there was no effect of reduced K nutrition on growth of inoculated plants. The reduction in growth in non-inoculated plants was accompanied by a similar reduction in K+ concentration in both roots and leaves and an overall 80% reduction of the plant potassium concentrations. In inoculated plants a 50% reduction occurred only in leaves. The expression of the K+ transporters HKT1;1, 1;2, 1;5, 2;2, 2;3 and 2;4 was up-regulated by the inoculation of B. megaterium under K deprivation conditions, explaining their higher K tissue concentrations and growth. Thus, the bacterial strain improved plant potassium nutrition without affecting K+ availability in the soil. The results demonstrate the potential of this bacteria for using as a biofertilizer to reduce the amount of potassium fertilizers to be applied in the field.
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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) | 0.001 | 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".