Insect netting: effect of mesh size and shape on exclusion of some fruit pests and natural enemies under laboratory and orchard conditions
Bibliographic record
Abstract
Abstract To improve exclusion systems for fruit trees, insect nets of various types were evaluated for their permeability to different beneficial and pest species, under laboratory and field conditions. Pests studied were the apple maggot, Rhagoletis pomonella (Diptera: Tephritidae) and the spotted wing drosophila, Drosophila suzukii (Diptera: Drosophilidae). Beneficials were Aphidoletes aphidimyza (Diptera: Cecidomyiidae), Aphidius matricariae (Hymenoptera: Braconidae) and Aphelinus abdominalis (Hymenoptera: Aphelinidae). Mesh nets with five different apertures (square, rectangle, triangle, rhombus and hexagon) and six different sizes (from 0.4 to 2.8 mm) were 3D-printed from strands of polylactic acid and tested in the laboratory along with two commercially available nets made of polyethylene. The physical and behavioral characteristics of the six studied species affected their ability to cross the nets. For an equal size (open area), the intrusion rate was generally greater through the square- and/or hexagonal-shaped meshes. Rectangular-shaped apertures totally excluded the apple maggot in both laboratory and field trials, provided their shortest side did not exceed 1.9 mm. For the spotted wing drosophila, a maximum of 1.0 mm was similarly required for exclusion in the laboratory. The shape factor (length/width ratio) of the apertures appeared to affect net selectivity. Field trials confirmed that more aphid predators and leafroller parasitoids colonized trees covered with larger mesh nets (2.3 × 3.4 mm), while still excluding the apple maggot. Thus, for a similar aperture size (area), an elongated rectangular-shaped mesh appears to facilitate access for beneficials, while continuing to provide effective protection against apple pests.
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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 | 0.000 | 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".