Susceptibility of <i>Eucalyptus</i> trees to defoliation by the <i>Eucalyptus</i> snout beetle, <i>Gonipterus</i> sp. n. 2, is enhanced by high foliar contents of 1,8‐cineole, oxalic acid and sucrose and low contents of palmitic and shikimic acid
Bibliographic record
Abstract
Gonipterus sp. n. 2 (Coleoptera, Curculionidae) is an invasive, commercially important weevil that causes large-scale defoliation of Eucalyptus trees. The weevil specifically feeds on young leaves and new shoots, thus reducing tree growth. The weevil displays a very strong preference for certain Eucalyptus genotypes, however, this behaviour and the chemistry underlying it is poorly understood, thereby complicating the selection of resistant trees. To elucidate the feeding preference of Gonipterus sp. n. 2, we assessed the relative levels of susceptibility of 62 Eucalyptus genotypes from 23 species using a laboratory choice assay. This revealed large intraspecific variation in susceptibility to weevil feeding, which for certain species, exceeded the interspecific variation. A semiquantitative metabolite profile analysis on 13 genotypes revealed strong correlations of 10 metabolites to feeding damage. The behavioural effects of the identified compounds were assessed through an in vitro feeding preference assay using artificial diets as well as under field conditions. This revealed three phagostimulants (1,8-cineole, oxalic acid and sucrose) and two feeding deterrent compounds (shikimic acid and palmitic acid) for Gonipterus sp. n. 2. These chemical markers can be applied to tree breeding programmes for the selection of resistant genotypes to reduce damage caused by Gonipterus weevils.
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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) | 0.000 | 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".