Evaluation of <i>Rhizobium</i> inoculant formulations for alfalfa yield and N fixation
Bibliographic record
Abstract
Because of its small seed size, alfalfa (Medicago sativa L.) typically is seeded at a shallow depth, putting Rhizobium inoculated onto the seed coat at a high risk of desiccation. Granular inoculants may provide a superior delivery formulation for Rhizobium because the inoculant can be placed deeper in the soil than the seed, where it is protected from desiccation. Sinorhizobium meliloti cv. Beaver delivered as (1) pre-inoculated alfalfa seed from the inoculant manufacturer, (2) commercial peat-based, self-sticking inoculant applied on-site, and (3) granular inoculant placed with the seed or (4) banded below and to the side of the seed was evaluated against uninoculated alfalfa controls at three field sites in Saskatchewan. Overall, alfalfa inoculated with the granular formulation placed below and to the side of the alfalfa seed was among the highest biomass producer in the establishment year, although it did not exhibit superior nodulation or biological N fixation compared with the other treatments. Any advantage conferred by the granular inoculant in the establishment year did not persist through the first and second production years. Under the conditions of this study, the delivery formulation had no long-term affect on alfalfa productivity, nodulation and biological N fixation. Furthermore, none of the inoculant treatments were consistently superior to the uninoculated controls. Key words: Alfalfa, granular inoculant, peat inoculant, pre-inoculated seed, Medicago sativa L., Sinorhizobium meliloti
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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) | 0.001 | 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".