Isolation and molecular characterization of non-Azotobacter bacteria using Azotobacter isolation protocols from pastures in the south of Turkey
Bibliographic record
Abstract
Isolation and molecular characterization of non-Azotobacter bacteria using Azotobacter isolation protocols from pastures in the south of Turkey Ebru ÇELEN ORCID: 0000-0002-8452-5933 Department of Biology, Faculty of Arts and Science, Bolu Abant İzzet Baysal University, Gölköy, 14280 Bolu, Türkiye Abstract Soil is a biodiversity-rich ecosystem. Nitrogen-fixing Azotobacter bacteria, an important component of this ecosystem, are frequently isolated using various methods. The aim of the present study was to perform partial molecular characterization of non-Azotobacter isolates derived during two Azotobacter isolation protocols, as well as to determine which bacteria can be obtained using this method. A total of 800 isolates were acquired from soil samples collected from various pastures in Antalya province of Turkey, with 92 of them being molecularly characterized. These isolates were clustered through RFLP analysis of 16S rRNA gene and the DNA sequences of the isolates representing different groups were performed. According to these results, the bacteria belonging to various genera (Agrobacterium, Phyllobacterium, Variovorax, Acinetobacter, Pseudomonas, Agromyces, and Arthrobacter) were identified. The results show that similar bacteria could be obtained through two isolation protocols used in this study. However, more diverse bacteria were encountered on the Brown-medium than on soil-past. Keywords: Azotobacter, isolate, soil, 16S rDNA ---------- ----------
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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".