Genotypic Differences in Root Hair Deformation and Subsequent Nodulation for Red Clover under Different Additions of Starter N Fertilization
Bibliographic record
Abstract
Abstract Red clover cultivars, including diploid and tetraploid, are commonly used in legume‐based pasture mixtures. However, information on nodulation under different starter N regimens is limited. We hypothesized that there is genetic variability among different red clover cultivars for nodulation. A root hair deformation assay was conducted using three diploid (AC Christie, Tapani and CRS15) and three tetraploid (Tempus, CRS18 and CRS39) red clover cultivars by inoculating them with Rhizobium leguminosarum biovar trifolii . Nodulation and morphological characteristics of two selected red clover cultivars, AC Christie and Tempus, were determined under five starter N concentrations (0, 0.2, 0.4, 0.8 and 1.6 mg per plant). Inoculation with rhizobia increased root hair deformation with significant interaction across cultivars. Nodulation was delayed under high starter N concentrations, and genotypic differences were evident for days‐to‐nodule initiation. There was a positive quadratic response to starter N for AC Christie and a negative quadratic response for Tempus for nodulation. Tempus had more active nodules (92 %) than AC Christie (73 %). The genetic variability of red clover cultivars should be considered in N fixation studies and their response to availability of initial N.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".