Factors Affecting Pollen Dispersal in High-density Apple Orchards
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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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 | 0.001 |
| 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 | 0.001 | 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".