Plant growth promoting rhizobacteria enhance growth and yield of chilli (Capsicum annuum L.) under field conditions.
Bibliographic record
Abstract
Plant growth promoting rhizobacteria (PGPR) can enhance the growth and productivity by exerting beneficial effects through direct and indirect mechanisms. The effect of PGPR on the growth and yield of chilli under field conditions has to date, not been substantiated. In this study, 15 bacteria were isolated from chilli rhizosphere and their morphological, biochemical, plant growthpromoting, and biocontrol characteristics were elucidated. Plant growth and yield attributes increased significantly when the 15 rhizospheric isolates were applied to a local chilli cultivar 'Suryamukhi' in pots. On the basis of their performance in the pot experiment, three rhizobacteria (C2, C25, and C32) were selected for further study in field. The 16S rDNA sequencing has identified C2 and C25 strains as Bacillus spp. and C32 strain as Streptomyces sp. Remarkable increase in growth characteristics such as total number of fruits, fruit-weight, and yield was recorded in plants with combined inoculation under field conditions. The results clearly demonstrate the rhizocompetence and plant growth enhancing efficacy of these strains. It can be surmised that the isolated strains have strong potential to be successful biofertilizers and bioenhacers.
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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".