Factors Affecting Pollen Dispersal in High-density Apple Orchards
Why this work is in the frame
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Bibliographic record
Abstract
Knowledge of pollen dispersal is essential for maximizing cross-fertilization in apples ( Malus × domestica Borkh.) and achieving optimal orchard design. Using allozyme markers, we examined dispersal of pollen from trees of a single cultivar (`Idared') throughout two apple orchards. In each orchard, the percentage of seeds sired by `Idared' was estimated for trees sampled at regular intervals along three transects, extending up to 18 rows (86 m) from the closest donor trees. The percentage of seed sired by `Idared' pollen ranged from 76% to 1% of seed sampled for a row. No differences in pollen dispersal were found among transects, despite differences in proximity to the bee colonies. Variation in `Idared' siring success was attributable to the cultivar of the fruit-bearing trees as well as their distance to the nearest `Idared' tree. Cultivar effects were associated with differences in flowering overlap, but not cross-compatibility with the pollenizer. Furthermore, flowering overlap was a good predictor of siring success only when the flowering times of competing pollenizer cultivars were also considered. The implications for orchard design are discussed.
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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 it