Insecticidal Activity of Bio-oil from the Pyrolysis of Straw from <i>Brassica</i> spp.
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
Agricultural crop residues can be converted through thermochemical pyrolysis to bio-oil, a sustainable source of biofuel and biochemicals. The pyrolysis bio-oil is known to contain many chemicals, some of which have insecticidal activity and can be a potential source of value-added pest control products. Brassicacae crops, cabbage, broccoli, and mustards, contain glucosinolates and isocyanates, compounds with recognized anti-herbivore activity. In Canada, canola Brassica napus straw is available from over 6 000 000 ha and mustard Brassica carinata and Brassica juncea straw is available from 200 000 ha. The straw can be converted by microbial lignocellulosic enzymes as a substrate for bioethanol production but can also be converted to bio-oil by thermochemical means. Straw from all three species was pyrolyzed, and the insecticidal components in the bio-oil were isolated by bioassay-guided solvent fractionation. Of particular interest were the mustard straw bio-oil aqueous fractions with insecticidal and feeding repellent activity to Colorado potato beetle larvae. Aqueous fractions further analyzed for active compounds were found not to contain many of the undesirable phenol compounds, which were previously found in other bio-oils seen in the dichloromethane (DCM) and ethyl acetate (EA) solvent phases of the present study. Identified within the most polar fractions were hexadecanoic and octadecanoic fatty acids, indicating that separation of these compounds during bio-oil production may provide a source of effective insecticidal compounds.
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