Genetic Variation in Seed Size and Germination Patterns and their Effect on White Spruce Seedling Characteristics
Bibliographic record
Abstract
Abstract We determined the degree to which families differ in seed and germination characteristics and examined the extent to which these characteristics influence the early growth of 75 open-pollinated white spruce families. Seed characteristics (1000-seed weight, length, width, area, volume) were measured for 400 seeds per family. Germination variables (germination capacity, peak value, germination value) were determined for each of the 75 families under controlled conditions and germination patterns were modelled using the Weibull function. Seedling characteristics (height, diameter, shoot and root dry weights) were measured at the end of the first and second growing seasons under standard nursery cultural practices. Statistically significant family variation (p < 0.0001) was found for all seed characteristics and germination variables measured. The between-family variance explained 23% to 98% of the total variance of morphological and physiological seed characteristics. Family differences at the seed stage explained up to 33% (root dry weight) and 12% (shoot dry weight) of the family differences observed at the one-year and two-year seedling stages, respectively. Since, in this study based on a comparison of family means, a maximum of only 12% of the family differences observed at the two-year seedling stage were explained by the effect of seed size, a selection for families with better juvenile characteristics could be envisaged without considering the maternal effect of seed size.
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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 | 0.001 | 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) | 0.000 | 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".