Shortening the generation cycle in faba bean (<i>Vicia faba</i>) by application of cytokinin and cold stress to assist speed breeding
Bibliographic record
Abstract
Abstract The aim of this study was to reduce the length of the breeding cycle for faba bean by accelerating seed setting. We examined the mode and time of exogenous 6‐benzylaminopurine (BAP) (cytokinin) application, and cold treatments and their combinations in two faba bean genotypes. Acropetal node number of pod and seed set and pollen viability were recorded during the experiments. Application of BAP improved pollen germination. The application of 10–5 M BAP 4 days after flowering increased seed set at the lower nodes. Cold treatment (8/4°C day/night for 2 days) after the onset of flowering induced the formation of more pods and faster pod set compared to the non‐cold treatment. The time to first seed was significantly reduced, and pollen viability was increased in plants exposed to cold treatment. Increased pollen viability also showed a significant positive correlation with seed setting. The combinations of 10–5 BAP and cold treatment together had similar and independent effects. These results will accelerate plant breeding in faba bean by providing additional tools for reducing generation time.
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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".