Genetic diversity of rhizobia nodulating <i>Trifolium ambiguum</i> in North America
Bibliographic record
Abstract
Kura clover (Trifolium ambiguum M.B.) is a persistent rhizomatous forage legume, whose use in the U.S.A. is limited by establishment difficulties in part attributable to nodulation problems. In this study, soil was collected from established stands of Kura clover growing in 9 diverse North American environments. Rhizobia were plant-trapped using Kura clover cv. Endura as host, then rhizobia from nodules fingerprinted using BOX-PCR. The diversity of isolates from North America was then contrasted to that of rhizobia from a single Caucasian environment (Russia), the center of origin for this species. Populations were characterized using clustering methods, and genetic diversity estimated using the Shannon-Weaver diversity index. The genetic diversity of the North American populations was extremely limited, all isolates being closely related to two of the strains found in a locally available commercial inoculant. In contrast, Russian isolates formed a distinct cluster with significant internal genetic diversity. Genetic diversity indices for the North American and Russian populations were 3.5 and 10.76, respectively. The implication of this and other studies is that Kura clover is highly specific in Rhizobium requirement. If the performance of this legume in the U.S.A. is to be improved, either by modifying current establishment practices or plant breeding, it is essential that these studies be paralleled by more collections and evaluation of rhizobia from its center of origin, given the extremely limited diversity of rhizobia found in North America.
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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".