Breaking Dormancy in Red Raspberry with Hot Water Treatment and its Effects on Cold Hardiness
Bibliographic record
Abstract
`Maurin Makea', `Muskoka', ` Ottawa', and `Preussen' red raspberry ( Rubus idaeus L.) canes were collected from the field and subjected to different hot water treatments (20, 35, 40, 45, and 50 °C) to determine if endodormancy could be removed by a near lethal stress. Estimation of days for 50% budbreak (DD 50 ) was found useful for describing the state of bud dormancy in the samples. Bud dormancy was broken in `Ottawa' by immersing the canes in 45 °C water for 2 hours, in `Maurin Makea' by treating the canes in 40 °C water, and in `Preussen' by both 40 and 45 °C treatments. The influence of this treatment on dormancy and cold hardiness at different times of the winter was further examined using `Ottawa' raspberry. The treatment removed bud dormancy most effectively in October, when the samples were in deepest dormancy. A slight effect was observed in November, but no effect in January. During ecodormancy in February the treatment delayed budbreak. Hot water treatment reduced cold hardiness of `Ottawa' canes by 8 to 15 °C, and that of buds by 9 to 13 °C during both endo- and ecodormancy. Based on the capacity of buds and canes to reacclimate, recovery from the stress treatment was possible at temperatures ≥4 °C. Loss of cold hardiness was caused by high treatment temperature itself and was not related to breaking of dormancy in samples. This finding suggests that dormancy and cold hardiness are physiologically unconnected in raspberry.
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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".