Temporal Changes in Abscisic Acid Concentration in Dormant and Non-Dormant Seeds of Wheat (Triticum spp.) Genotypes
Bibliographic record
Abstract
Little is known about the levels and physiological role of endogenous abscisic acid (ABA) during after-ripening and germination. Genetic variants for ABA content were investigated to account for the role of ABA in the persistence of seed dormancy. In this study, genotypic variation in ABA contents at Zadok’s Growth Stage 92 (ZGS 92), temporal changes in ABA during two physiological stages (after-ripening and water uptake), and responsiveness of wheat seed to applied ABA at different concentrations, of two tetraploid and two hexaploid wheat genotypes were examined during 1996 and 97. A combined analysis of variance indicated no significant differences in ABA among genotypes at ZGS 92. During the early stages of germination, endogenous ABA in the caryopses of the four wheat genotypes was analyzed. The results showed a transient increase in ABA content (up to 4 hours) occurring first during imbibition, followed by a decline up to 12 hours and an increase thereafter. ABA declined in all genotypes during seven weeks of after-ripening (dry storage). The four genotypes had reductions in ABA up to 4 weeks of after-ripening. An increase in ABA was observed during the fourth and fifth weeks of after-ripening with a decline after seven weeks. ABA had a little effect on germination index at the lower temperature (10 °C). Our results suggested that wheat grains are able to synthesize ABA during imbibition. However, no significant differences between dormant and non-dormant genotypes were detected. A decrease in ABA during after-ripening could have a role in loss of seed dormancy.
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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) | 0.000 | 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 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".