Insect pollinators of conference pear (<i>Pyrus communis</i> L.) and their contribution to fruit quality
Bibliographic record
Abstract
The pear (Pyrus communis L.) cultivar, Conference, is parthenocarpic but misshapes and marketable fruit losses of 6% at harvest are common. In other studies, insect flower visitors are identified as important for apple quality, but far fewer studies have examined the effects of insects and cross-pollination on pear quality. Using a range of replicated field experiments, this project aimed to determine the; 1) biodiversity of pear blossom insect visitors, 2) pollen limitation and fruit quality as a function of distance from the orchard edge and number of insect visitors, and 3) importance of cross pollination on fruit quality. A wide range of insects, >30 species, visited pear flowers including honey bees, bumble bees, solitary bees and hoverflies. Honey bees were the most frequent visitors, but all guilds, to a greater or lesser extent, made contact with the reproductive parts of the flower. Insect visits resulted in ~10% higher fruit set. There was no effect of distance from the edge (up to 50 m) of orchard on the quality of pears, and no consistent difference in the guild of insects visiting at distances from the orchard boundary. Cross-pollination with the variety Concorde produced better quality Conference fruits. We discuss how pollination of Conference pears could be managed to improve yields of marketable fruit.
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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 | 0.001 | 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".