Optimizing aphid biocontrol with the predator <i>Aphidoletes aphidimyza</i>, based on biology and ecology
Bibliographic record
Abstract
Aphidoletes aphidimyza is one of the most important predators used in the augmentative biological control of aphids, key pests of many crops worldwide. Adult females are very efficient in locating aphid infestations over a relatively long range, up to 45 m, and deposit eggs near or within aphid colonies. The predatory larvae are aphid generalists preying on several agriculturally important aphid species. The successful use of this biocontrol agent in agricultural systems depends on several biotic and abiotic factors. Among biotic factors, aphid species, plant structure, interspecific competition and intraguild predation may significantly impact the predator´s population dynamics. Key abiotic conditions include day lengths (above a critical threshold to prevent diapause), availability of mating sites in the crop, temperature (above 15 °C to enable egg laying), air relative humidity (above 70%) and availability of pupation sites. Although several successes have been reported in open field crops with naturally occurring or released populations, commercial releases are primarily used in protected crops. Optimized emergence boxes combining provisioning of food sources for the adults, integration with the technological advances that occurred in the greenhouse environment lately, insights into the nutritional ecology in open field crops and exploration of the genetic variability are proposed as future directions to improve adoption and efficacy of A. aphidimyza in crop protection. © 2018 Society of Chemical Industry.
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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 | 0.000 | 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".