Comparison of pre-treatments for inducing germination in highly dormant wheat genotypes
Bibliographic record
Abstract
An effective dormancy-breaking method may be of interest to wheat (Triticum aestivum L.) breeders selecting for increased seed dormancy prior to advancing their populations in greenhouse grow-outs. The objective of this study was to identify an effective pre-treatment for breaking dormancy in wheat that did not result in seedling etiolation. In 2000, eight dormant (W98616, line 211, EMDR-4, EMDR-9, EMDR-14, RL4137, Columbus, and AC Domain) and one nondormant line (Roblin) were grown at two locations in Saskatchewan. Seeds were: (i) stored for zero to 21 wks at 24°C before incubating at 20°C for 7 d; (ii) incubated at 5, 10, 15, 20, and 25°C for 14 d; and (iii) treated with gibberellic acid (GA3) (0.0006 and 0.0014 M), potassium nitrate (KNO3) (0.01 and 0.02 M), chilling, heating, chilling with 0.01 M KNO3, and heating with 0.01 M KNO3 before incubating at 10°C for 14 d. Seedling growth was observed in a duplicated growth chamber experiment. Seedling length, first inter-node length, and biomass yield data were collected from plants grown from seeds treated with four effective pretreatments. Data were subjected to an ANOVA. Six to 18 weeks of storage at 24°C were required to break the dormancy (≥ 95% germination) in dormant genotypes. Incubation at 10°C was the most effective temperature for promoting germination in dormant seeds after 10d of testing. Four pre-treatments including 0.0006 M GA3, 0.0014 M GA3, chilling with 0.01 M KNO3, and heating with 0.01 M KNO3 led to ≥ 95% germination within 10 d of testing. Only GA3 treatments were associated with etiolated seedling growth. Heating with 0.01 M KNO3 or chilling with 0.01 M KNO3, applied before incubating at 10°C in darkness, may be of interest to breeders selecting for increased dormancy before advancing breeding populations in greenhouse grow-outs. Key words: Triticum, dormancy, nitrate, chilling, heating, etiolated seedling
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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) | 0.000 | 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 | 0.001 |
| 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".