Expanding agricultural potential through biological nitrogen fixation: Recent advances and diversity of diazotrophic bacteria
Bibliographic record
Abstract
Biological nitrogen fixation (BNF) by diazotrophic bacteria is one of the oldest and most crucial processes in nature. In this process, bacteria form symbiotic associations with plants, capturing atmospheric nitrogen and making it readily available to them. The diversity of nitrogen-fixing bacteria is vast. Recent advancements in molecular biology techniques have enabled the identification of new genera and species capable of fixing nitrogen and providing other types of nutrients for plants. From an agronomic perspective, this process is fundamental in increasing crop productivity sustainably and -cost-effectively. This review aims to categorize the most recent updates on the diversity of nitrogen-fixing bacteria and showcase the main advances in the genetic improvement of legumes for this characteristic. Recent research has revealed a wide diversity of species applicable to various crops of agronomic interest, and many of these bacteria have been used either alone or in consortium with other microorganisms. This study demonstrates the agricultural potential of these new discoveries and the vast possibilities for expanding research into the diversity of microorganisms responsible for BNF in 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".