Impact of sap-sucking insect pests (Blastopsylla occidentalis Taylor and Glycaspis brimblecombei Moore, Hemiptera: Psyllidae) on unifloral eucalyptus honey
Bibliographic record
Abstract
Eucalyptus species are important worldwide as melliferous plants, as a source of nectar and pollen, and contribute to the production of large quantities of honey, especially in summer when E. Camaldulensis Dhnh., the most common eucalyptus species in the Mediterranean area, flowers. Its honey yield potential exceeds 200 kg/ha, sometimes accounting for more than 50% of total apiary production. In Italy, eucalyptus plantations cover at least 50,000 hectares, corresponding to a potential production of 10,000 tons of honey per year. Since 2000 several invasive eucalyptus pests have spread and settled in the Mediterranean. Of these, psyllids Blastopsylla occidentalis Taylor and Glycaspis brimblecombei Moore have become major threats to eucalyptus plantations. The main objective of this study was to verify the impact of sap-sucking insects unifloral eucalyptus honey production and quality in Northern Sardinia (Italy). Our results show that a pronounced decrease in honey production occurred after 2011, with no production at all in 2012 and 2013, partial recovery in 2014-2016 and a further increase in 2017 and 2018. Moreover, the incidence of honeydew produced by psyllids has led to modifications in the chemical-physical characteristics and pollen spectrum of unifloral eucalyptus honey.
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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".