Influence of photoperiod response on the expression of cold hardiness in wheat and barley
Bibliographic record
Abstract
Vernalization and photoperiod requirements regulate the timing of the vegetative/reproductive transition in plants. Cereals adapted to cold winter climates regulate this developmental transition mainly through vernalization requirements, which delay transition from the vegetative to the reproductive growth stage. Recent research indicates that vernalization requirements also influence the expression of low-temperature (LT) tolerance genes in cereals exposed to acclimating temperatures. The objective of the present study was to determine if LT tolerance expression was also developmentally regulated by photoperiod response. The nonhardy, short day (SD) sensitive, wheat (Triticum aestivum L. em Thell) cultivar AC Minto, the LT tolerant, highly SD sensitive barley (Hordeum vulgare L.) cultivar Dicktoo, and a barley selection with very low sensitivity to SD were subjected to 8-h (SD) and 20-h (LD) days at cold acclimating temperatures over a period of 98 d. Final leaf number (FLN) was used to measure photoperiod sensitivity and determine the vegetative/reproductive transition point. The LT tolerance of the less SD sensitive barley genotype was similar for LD and SD treatments. In contrast, a delay in the transition from the vegetative to the reproductive stage in AC Minto and Dicktoo grown under SD resulted in an increased level and/or longer retention of LT tolerance. These results support the hypothesis that not only the level, but also the duration of gene expression determines the degree of LT tolerance in cereals. Consequently, any factor that lengthens the vegetative stage, such as vernalization or photoperiod sensitivity, also increases the duration of expression of LT tolerance genes. Key words: Triticum aestivum L., Hordeum vulgare L., low-temperature tolerance, photoperiod, developmental regulation
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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".