Genetic and phenotypic diversity of rhizobia nodulating chickpea (<i>Cicer arietinum</i> L.) in soils from southern and central Ethiopia
Bibliographic record
Abstract
Forty-two chickpea-nodulating rhizobia were isolated from soil samples collected from diverse agro-ecological locations of Ethiopia and were characterized on the basis of 76 phenotypic traits. Furthermore, 18 representative strains were selected and characterized using multilocus sequence analyses of core and symbiotic gene loci. Numerical analysis of the phenotypic characteristics grouped the 42 strains into 4 distinct clusters. The analysis of the 16S rRNA gene of the 18 strains showed that they belong to the Mesorhizobium genus. On the basis of the phylogenetic tree constructed from the combined genes sequences (recA, atpD, glnII, and gyrB), the test strains were distributed into 4 genospecies (designated as genospecies I-IV). Genospecies I, II, and III could be classified with Mesorhizobium ciceri, Mesorhizobium abyssinicae, and Mesorhizobium shonense, respectively, while genospecies IV might represent an unnamed Mesorhizobium genospecies. Phylogenetic reconstruction based on the symbiosis-related (nifH and nodA) genes supported a single cluster together with a previously described symbiont of chickpea (M. ciceri and Mesorhizobium mediterraneum). Overall, our results corroborate earlier findings that Ethiopian soils harbor phylogenetically diverse Mesorhizobium species, justifying further explorative studies. The observed differences in symbiotic effectiveness indicated the potential to select effective strains for use as inoculants and to improve the productivity of chickpea in the country.
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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 | 0.001 |
| 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".