Testing Natural Products for Toxicity against Agricultural Pests and Pathogens
Bibliographic record
Abstract
In a constant race to overcome pesticide resistance by pests and pathogens, this research aimed to discover bioactive inhibitory compounds from natural products.I tested extracts from 10 different fungal isolates that were previously shown to have antifungal activity, and 5 commercially available natural products.Assays were developed to test natural products for antibiotic activities against model pathogens and pests including fungi, insects, and molluscs.The objectives of this research were to develop and determine the effectiveness of bioassays, and to identify potentially interesting natural products.Of the 10 fungal isolates tested, reconstituted broths of Penicillium virgatum, Ramularia vizellae, and Trichoderma sp.showed pronounced anti-fungal activity.Further, P. virgatum and Trichoderma sp.shows anti-insect activity while broths of Ramularia vizellae and Trichoderma sp.exhibited anti-mollusc activity.A preliminary metabolomic study identified potentially interesting metabolites that requires further investigation to determine the chemical structure(s), mode of action, and other attributes.
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.
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) | 0.001 | 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) | 0.003 | 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".