Characterization of soybean bradyrhizobia for which serogroup affinities have not been identified
Bibliographic record
Abstract
The USDA, ARS National Rhizobium Germplasm Collection contains 143 accessions of slow-growing soybean strains among which there are 17 distinct serological groups. However, 11 strains appear to have no serological affinity with the 17 serogroups. Therefore, we determined whether these strains were diverse and examined their phylogenetic placement. Nine strains formed nitrogen-fixing symbioses with soybean indicating that these accessions were not contaminants. We concluded from results of amplified fragment length polymorphism (AFLP) analysis, using 3 selective primers with 8 strains, that they were genetically dissimilar. Nine strains were examined for their fatty acid composition using fatty acid methyl ester (FAME) derivatives. The FAME results with 5 strains and serotype strains of Bradyrhizobium elkanii were similar, while results with each of the remaining 2 pairs were either similar to the type strain of Bradyrhizobium japonicum (USDA 6) or to USDA 110. Evolutionary history of 9 strains was reconstructed from sequence divergence of a combination of the complete 16S rRNA gene, the internally transcribed spacer region, and about 400 bases of the 5' end of the 23S rRNA gene. Placement of 5 strains was nested within B. elkanii, 2 with USDA 110, and the other 2 with USDA 6. We concluded that soybean isolates that cannot be placed within one of the 17 established serogroups are phenotypically and genetically as diverse as the serotype strains.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".