Integrated pest management in cotton: exploiting behaviour-modifying (semiochemical) compounds for managing cotton pests
Bibliographic record
Abstract
We review here research on semiochemicals for cotton pest management carried out in successive Cotton Co-operative Research Centres from 1998 to 2012. Australian cotton is now dominated by transgenic (Bt) varieties, which provide a strong platform for integrated pest management of key pests such as Helicoverpa spp., but new technologies are required to manage the development of resistance in Helicoverpa spp. to transgenic cotton and the problems posed by emerging and secondary pests, especially sucking insects. A long-range attractant for Helicoverpa moths, based on plant volatiles, has been commercialised as Magnet®. The product has substantial area-wide impacts on moth populations, and only limited effects on beneficial insects. Potential roles are being investigated for this product in resistance management of Helicoverpa spp. on transgenic cotton. Short-range, non-volatile compounds on organ surfaces of plants that do not support development of Helicoverpa spp. have been identified; these compounds deter feeding or oviposition, or are toxic to insect pests. One such product, Sero X®, is effective on Helicoverpa spp. and sucking pests such as whiteflies (Bemisia tabaci), green mirids (Creontiades dilutus), and other hemipteran insects, and is in the advanced stages of commercialisation.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".