Isolation, Characterization, Screening, Formulation and Evaluation of Plant Growth Promoting Rhizobacteria
Bibliographic record
Abstract
Plant growth promoting rhizobacteria (PGPR) are bioresources which may be viewed as a novel and potential tool for providing substantial benefits to the agriculture. Soil is the dynamic living matrix and the major source of food security providing various resources of plant growth and maintaining life processes. PGPR are originally defined as root-colonizing bacteria that cause either plant growth promotion or biological control of plant diseases. Chemical fertilizers are used for killing pathogens, increase crop yield but long term use of chemical fertilizers lead to adverse effect to the soil profile and is the reason for decrease in soil productivity, on the other hand PGPR promote plant growth directly by either facilitating resource acquisition (nitrogen, phosphorus and essential minerals) or modulating plant hormone levels, or indirectly by decreasing the inhibitory effects of various pathogens on plant growth and development in the forms of biocontrol agents. PGPR is the indispensable part of rhizosphere biota that when grown in association with the host plants can stimulate the growth of the host. PGPR seemed as successful rhizobacteria in getting established in soil ecosystem due to their high adaptability in a wide variety of environments, faster growth rate and biochemical versatility to metabolize a wide range of natural and xenobiotic compounds. Isolated PGPRs from selective crop rizosphere soil were used for further growth promotion and biocontrol studies in the green house and field. Different studies have been carrying out to develop some new bioformulations and evaluate their efficacy in promoting crop seedlings growth characteristics. Field trials were performed to evaluate selective crops with formulations of several plants PGPR in a production system. The present review highlights the Plant growth promoting rhizobacteria as an alternative of chemical fertilizer for sustainable, environment friendly agriculture.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".