Root nodule bacteria from <i>Clitoria ternatea</i> L. are putative invasive nonrhizobial endophytes
Bibliographic record
Abstract
In this study, bacteria (8 species and 5 genera) belonging to the classes Betaproteobacteria, Gammaproteobacteria, and Sphingobacteria were isolated from root nodules of the multipurpose legume Clitoria ternatea L. and identified on the basis of partial 16S rRNA sequencing. The root nodule bacteria were subjected to phenotypic clustering and diversity studies using biochemical kits, including Hi-Media Carbokit™, Enterobacteriaceae™ identification kit, ERIC-PCR, and 16S ARDRA. All the strains showed growth on Ashby's N-free media over 7 generations, indicative of presumptive nitrogen fixation and further confirmed by amplification of the nifH gene. None of the strains showed the capability to renodulate the host plant, neither alone nor in combination with standard rhizobial strains, which was further confirmed by the absence of nodC bands in PCR assay. The results clearly indicate the common existence of nonrhizobial microflora inside the root nodules of legumes, which were thought to be colonized only by rhizobia and were responsible for N2 fixation in leguminous crops. However, with the recent discovery of nodule endophytes from a variety of legumes, as also observed here, it can be assumed that symbiotic rhizobia are not all alone and that these invasive endophytes belonging to various bacterial genera are more than just opportunistic colonizers of specialized nodule niche.
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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) | 0.000 | 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 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".