Cold Acclimation Threshold Induction Temperatures in Cereals
Why this work is in the frame
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Bibliographic record
Abstract
To acquire a competitive advantage and ensure survival when exposed to low‐temperature extremes, cool season plants must be programmed to respond to temperatures favorable for growth and environmental cues that signal seasonal changes. This project was initiated to determine (i) the cold acclimation threshold induction temperatures (ITs) in wheat ( Triticum aestivum L.), barley ( Hordeum vulgare L.), and rye ( Secale cereale L.) and (ii) their relationship to plant freezing tolerance at full acclimation. A wide range of genotypic specific IT and initial rapid acclimation responses that were inversely related to decreases in temperatures below the threshold was observed both within and among species, indicating that cereals monitor temperature with a high level of precision. Hardy wheat cultivars had a 5.7°C warmer activation temperature than tender genotypes when the vernalization gene was neutralized in near‐isogenic lines, and a 12°C difference in IT of hardy rye compared with tender barley cultivars emphasized the high cold adaptation potential of rye. This early response to decreasing temperatures means that hardy rye had a longer time to prepare for the extremes of winter and was in a better position to cope with unexpected frosts during the growing season. Differences in IT were closely related to the differences in freezing tolerance at full acclimation. However, a longer vegetative stage also meant that winter habit genotypes were more responsive to extended periods at acclimation temperatures in the threshold range.
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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 | 0.001 |
| 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 it