Phosphate Solubilizing Bacteria: A potential biotic component for solubilizing phosphate in soil and its application as Biofertilizer: A Review
Bibliographic record
Abstract
The number of populations is increasing day by day. As populations no is being increased, the demand of food is also increasing simultaneously. Therefore, it’s easy to understand that no. of population growing is directly proportional to the demand of food. To increase the yield of food crops a large amount of chemical fertilizers is used every year. But certainly, these chemical fertilizers can cause long term damage to environment as well as on the bodies of those who will consume the grains also. In that case definitely we have to think some alternatives of chemical or artificial fertilizers. In addition, in spite of presence of sufficient amount of phosphate in soil, plant can’t get the access of phosphate as it forms complex with either inorganic metal ion or various organic compounds. On that note scientists and researchers have studied some microorganisms which can play very significant role in this critical situation. This microorganism live in rhizosphere region of plant and can increase soil fertility by solubilizing phosphate and also help in the development of plant. These are known as Phosphate Solubilizing Bacteria (PSB). This review discussed the different species of PSB, the mechanisms they follow to solubilize phosphate, their role in plant development. This research review also focuses on use of phosphate solubilizing bacteria for sustainable agricultural purpose.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".