Effect of water stress on germination of beechnuts treated before and after storage
Bibliographic record
Abstract
Beechnuts from two seedlots were pretreated, without medium, at a controlled moisture content (MC) of 30% before or after 1-year storage at 7 °C. Seeds treated with the two methods were germinated on substrates at decreasing osmotic potential down to 1.2 MPa. A moderate stress of 0.2 MPa caused a slight but significant decrease in germination percentage. Each further increment in water stress produced additional significant decreases in germination capacity. At 1.2 MPa, germination was almost prevented. Seeds pretreated before storage showed lower germination percentage and speed at all osmotic potentials, but this result was due to a marked effect of seed initial MC, rather than a lower resistance to water deficit. In fact, MC of beechnuts pretreated before storage was 8%, whereas beechnuts pretreated after storage started germination tests under water stress with an initial MC of 30%. Moreover, seeds at lower initial MC need more time to imbibe before the germination process can start. Seeds with higher initial MC were probably able to cope better with water deficit, at least during the 30-day germination test in the laboratory. A second experiment carried out on beechnuts treated only before storage but made to have different initial MC seemed to confirm this conclusion. Ungerminated seeds were not damaged, as revealed by a tetrazolium test performed at the end of each germination test. Advantages in nursery practice shown by dry, nondormant beechnuts (pretreated before storage) are discussed in relation to the possibility of sowing when water availability in the soil is not a limiting factor.
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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 | 0.000 |
| 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".