Investigating properties of sweet cherry (<i>Prunus avium</i>) flower buds that help promote freezing avoidance by supercooling
Bibliographic record
Abstract
Mechanisms involved in the supercooling of plant tissues as a means of low temperature survival are still not fully understood. We investigated properties that may promote supercooling in overwintering sweet cherry (Prunus avium) flower buds. We conducted experiments on sweet cherry flower buds using differential thermal analysis (DTA) and observed locations of ice formation in the bud structure. We also used anatomical development and water-soluble dye uptake throughout the overwintering period to identify changes that correlate with gain and loss of supercooling capacity. Our results revealed barriers to ice propagation are likely unique to each primordium, as inferred from exotherms produced from buds subjected to DTA, although multiple primordia may freeze simultaneously. Ice is accommodated between the bud scales and within the bud axis; however, full expression of supercooling was not dependent on the presence of scales. Anatomical and DTA studies revealed a correlation between vascular differentiation in primordia and loss of supercooling in the spring; these observations were at a higher temporal resolution than previously described for Prunus. Furthermore, disturbing tissues subtending the primordia interfered with typical patterns of supercooling, indicated more erratic and numerous exotherms produced during DTA. In summary, sweet cherry flower buds undergo extra-organ freezing. In winter, a barrier to ice propagation in the region directly subtending primordia protects the flower from freezing damage, but in the spring xylem differentiation in primordia provides a conduit for ice propagation that compromises supercooling.
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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".