Induction of tolerance to fast desiccation in black spruce (<i>Picea mariana</i>) somatic embryos: relationship between partial water loss, sugars, and dehydrins
Bibliographic record
Abstract
Events associated with the induction of tolerance to fast desiccation in black spruce (Picea mariana) somatic embryos were investigated. An experimental approach using an initial period of partial water loss was developed to induce either no, partial, or complete tolerance to fast desiccation. Tolerance to subsequent fast desiccation was not promoted by decreasing embryo water content from 1.5 to 1.1 g H2O g-1 DW (g g-1) throughout the first 24 h of slow desiccation. However, tolerance increased from 10 to 95% germination during the second 24-h period of slow desiccation after partial water loss from 1 to 0.55 g g-1. Emphasis was also placed on the relationship between observed tolerance, and sugar and dehydrin contents. Compared to controls, sucrose content in embryos doubled after 24 h of slow desiccation and more than tripled after 48 h. Conversely, starch content was decreased by one half after 24 h and by three quarters after 48 h. Sucrose abundance and raffinose occurrence after 48 h of slow desiccation were congruent with complete tolerance to fast desiccation. The period of slow desiccation between 24 and 48 h also increased the content of a 24-kDa dehydrin and the appearance of a 42-kDa dehydrin. The relationship between partial water loss, sugars and dehydrins is discussed with respect to tolerance to fast desiccation in black spruce somatic embryos.
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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".