Efficacy of Oil and Photosensitizer against Frankliniella occidentalis in Greenhouse Sweet Pepper
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Many common insect pests have developed resistance against the pesticides currently available, to the point where pest and disease management has become extremely difficult and expensive, increasing pressure on agriculture and food production. There is an urgent need to explore and utilize alternatives. Due to their unique mode of action, photosensitizers may be able to control insect pests effectively, especially in combination with oil-based products, without the risk of resistance build-up. In this study, the efficacy of a mineral oil-based horticultural spray oil, PureSpray™ Green (PSG), and a sodium magnesium chlorophyllin photosensitizer formulation, SUN-D-06 PS, were evaluated and compared to a registered cyantraniliprole insecticide (as positive control) and a negative control against western flower thrips (WFT), Frankliniella occidentalis. In detached leaf ingestion assays, PSG at high concentration was more effective than low concentration, causing >70% WFT mortality, whilst SUN-D-06 PS + PSG caused higher mortality than cyantraniliprole after five days of feeding. The same combination was as effective as cyantraniliprole in the contact assay. In greenhouse pepper, the photosensitizer decreased the WFT more than mineral oil applied alone, whilst a combination treatment of SUN-D-06 PS + PSG was most effective, decreasing the WFT population to fewer than four WFT per plant. SUN-D-06 PS + PSG shows promise as a sustainable, economical way of controlling WFT, with the potential to be incorporated into existing integrated pest (and disease) management (IPM) programs with ease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it