Isolation and identification of salt-tolerant plant-growth-promoting rhizobacteria and their application for rice cultivation under salt stress
Bibliographic record
Abstract
Growth and productivity of rice are negatively affected by soil salinity. However, some salt-tolerant rhizosphere-inhabiting bacteria can improve salt resistance of plants, thereby augmenting plant growth and production. Here, we isolated a total of 53 plant-growth-promoting rhizobacteria (PGPR) from saline and non-saline areas in Bangladesh where electrical conductivity was measured as >7.45 and <1.80 dS/m, respectively. Bacteria isolated from saline areas were able to grow in a salt concentration of up to 2.60 mol/L, contrary to the isolates collected from non-saline areas that did not survive beyond 854 mmol/L. Among the salt-tolerant isolates, Bacillus aryabhattai, Achromobacter denitrificans, and Ochrobactrum intermedium, identified by comparing respective sequences of 16S rRNA using the NCBI GenBank, exhibited a higher amount of atmospheric nitrogen fixation, phosphate solubilization, and indoleacetic acid production at 200 mmol/L salt stress. Salt-tolerant isolates exhibited greater resistance to heavy metals and antibiotics, which could be due to the production of an exopolysaccharide layer outside the cell surface. Oryza sativa L. fertilized with B. aryabhattai MS3 and grown under 200 mmol/L salt stress was found to be favoured by enhanced expression of a set of at least four salt-responsive plant genes: BZ8, SOS1, GIG, and NHX1. Fertilization of rice with osmoprotectant-producing PGPR, therefore, could be a climate-change-preparedness strategy for coastal agriculture.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".