The Relationships between Plant Developmental Traits and Winter Field Survival in Rye (Secale cereale L.)
Bibliographic record
Abstract
Overwintering cereals accumulate low temperature tolerance (LTT) during cold acclimation in the autumn. Simultaneously, the plants adjust to the colder season by making developmental changes at the shoot apical meristem. These processes lead to higher winter hardiness in winter rye varieties (Secale cereale L.) adapted to Northern latitudes as compared to other cereal crops. To dissect the winter-hardiness trait in rye, a panel of 96 genotypes of different origins and growth habits was assessed for winter field survival (WFS), LTT, and six developmental traits. Best Linear Unbiased Estimates for WFS determined from five field trials correlated strongly with LTT (r = 0.90, p < 0.001); thus, cold acclimation efficiency was the major contributor to WFS. WFS also correlated strongly (p < 0.001) with final leaf number (r = 0.80), prostrate growth habit (r = 0.61), plant height (r = 0.34), but showed weaker associations with top internode length (r = 0.30, p < 0.01) and days to anthesis (r = 0.25, p < 0.05). The heritability estimates (h2) for WFS-associated traits ranged from 0.45 (prostrate growth habit) to 0.81 (final leaf number) and were overall higher than for WFS (h2 = 0.48). All developmental traits associated with WFS and LTT are postulated to be regulated by phytohormone levels at shoot apical meristem.
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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 | 0.001 | 0.001 |
| 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".