Combination of protein-rich pea flour and pea extract with insecticides and enzyme inhibitors for control of stored-product beetles
Bibliographic record
Abstract
Abstract Protein-rich pea flour and its extract are toxic to stored-product beetles and, at a concentration of 0.1%, can control these insects in a granary. To reduce the concentration of protein-rich pea flour needed to control stored-product beetles, natural products or currently used grain protectants (diatomaceous earth, neem, Bacillus thuringiensis (Berliner), malathion, and pyrethrum) were mixed with protein-rich pea flour in wheat. Mixtures were tested against the rice weevil, Sitophilus oryzae (L.) (Coleoptera: Curculionidae), the red flour beetle, Tribolium castaneum (Herbst) (Coleoptera: Tenebrionidae), and the rusty grain beetle, Cryptolestes ferrugineus (Stephens) (Coleoptera: Cucujidae). Neem and protein-rich pea flour acted synergistically against T. castaneum. Malathion and protein-rich pea flour acted synergistically against S. oryzae. Protein-rich pea flour combined with diatomaceous earth or pyrethrum acted additively against S. oryzae. All other combinations acted antagonistically. An extract from protein-rich pea flour reduced feeding of S. oryzae, and three enzyme inhibitors, piperonyl butoxide, profenofos, and diethyl maleate, were tested for their possible synergistic effects on feeding deterrence and mortality. Piperonyl butoxide and pea extract had additive effects, and diethyl maleate had no effect on the feeding and mortality of insects. Profenofos alone killed all insects in 3 days. The flour consumption of S. oryzae was positively correlated with LT50 (time to 50% mortality) in flour disks treated with pea extract.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".