Changes in carbohydrates and freezing tolerance during cold acclimation of red raspberry cultivars grown in vitro and in vivo
Bibliographic record
Abstract
Changes in LT50 and carbohydrate levels in response to cold acclimation were monitored in vitro and in vivo in red raspberry ( Rubus idaeus L.) cultivars with different levels of cold hardiness. Entire micropropagated plantlets or shoot tips from 3 cultivars were harvested before, during and after cold acclimation. Cane samples from container‐grown plants of 4 cultivars were harvested before and during cold acclimation and deacclimation. Samples were evaluated for cold hardiness (LT50) by controlled freezing, then analyzed for carbohydrates, including starch, sucrose, glucose, fructose and raffinose. Hardiness of cold‐acclimated ‘Muskoka’ and ‘Festival’ was superior to that of ‘Titan’ or ‘Willamette’. In vitro plantlets had higher levels of soluble carbohydrates on a dry weight basis and higher ratios of sucrose:(glucose+fructose) than the container‐grown plants. Total soluble carbohydrates, primarily sucrose, accumulated during cold acclimation in both plantlets (33–56% relative increase) and plants (143–191% relative increase). Sucrose increased 124–165% in plantlets and 253–582% in container‐grown plants during acclimation and declined rapidly to the level of control plants during deacclimation. Glucose and fructose also accumulated, but to a lesser extent than sucrose. Raffinose concentrations were very low, but increased significantly during cold acclimation. In vitro, genotype hardiness was related to the high concentrations of total soluble carbohydrates, sucrose and raffinose. In vivo, hardier genotypes had lower concentrations of starch than the less hardy genotypes. These results demonstrated the importance of soluble carbohydrates, especially sucrose, in cold hardening of red raspberry and that the in vitro conditions or controlled acclimation conditions do not necessarily reflect the phenomena observed in vivo.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".