<i>Ensifer meliloti</i>is the preferred symbiont of<i>Medicago arborea</i>in eastern Morocco soils
Bibliographic record
Abstract
Polyphasic characterization of 61 bacteria isolated from root nodules of Medicago arborea (Medic tree) plants growing in 4 arid soils of the arid eastern area of Morocco was studied. All the isolates characterized were fast growers. The phenotypic, symbiotic, and cultural characteristics analyzed allowed the description of a broad physiological diversity among the isolates. The results obtained suggest that the phenotype of these rhizobia might have evolved to adapt to the local conditions. The genetic characterization consisted of an analysis of the rep-PCR (repetitive extragenic palindromic polymerase chain reaction) fingerprints and a PCR-based RFLP (restriction fragment length polymorphism) of the 16S rDNA patterns. The diversity of the isolates was investigated by rep-PCR, giving a similarity of 62%, delineated into 3 clusters, 4 groups, and 6 subclusters. This wide diversity was also observed by a phenotypic approach, where the carbohydrate assimilation test was the most discriminating. The results show a relationship between rep-PCR fingerprinting and sugar assimilation, which are complementary in diversity investigation. The nearly complete 16S rRNA gene sequence from representative strains of each soil showed they are closely related to members of the genus Ensifer of the family Rhizobiaceae within the Alphaproteobacteria and shows the highest similitude values (99.93%/100%) with Ensifer meliloti LMG 6133(T) (X67222). Sequencing of the symbiotic nodC gene from 7 representative strains revealed they had 94.89% identity with the nodC sequence of the type strain E. meliloti LMG 6133(T) (EF428922). Therefore, the 61 M. arborea isolates from the 4 different soils have the same phylogenetic affiliation, which proves the restricted host specificity among M. arborea species.
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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 | 0.001 | 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".