Epigenetic control of seed development and dormancy in cereals
Bibliographic record
Abstract
Seeds, which are imperative for the propagation of seed plants, are also of major nutritional and economic value in agriculture. The precise dormancy and germination of crop seeds are important traits for modern agriculture. Pre-harvest sprouting (PHS) or the germination of seeds while attached to the plant before harvest, is a significant problem in crops, particularly in cereals. Therefore, understanding the various mechanisms of seed development and dormancy are imperative. While the molecular and hormonal aspects of seed dormancy are well understood, the role of epigenetic pathways is just beginning to unravel, particularly for cereal crops. The majority of this information has been generated in Arabidopsis; however, there is increasing focus on cereal crops such as rice and maize. Other important cereal crops, such as wheat and barley, lag behind even though seed dormancy and PHS are even more critical for these crops. Similarly, while much progress has been made in understanding the role of histone modifications in seed development, the role of DNA methylation has not been well investigated. In this article, we review the progress made in uncovering the role of epigenetic modifications in cereal crops with reference to knowledge generated in Arabidopsis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".