Insecticidal Components from Field Pea Extracts: Soyasaponins and Lysolecithins
Bibliographic record
Abstract
Extracts from field peas (Pisum sativum L.) have previously been shown to have a utility to control insect pests. To identify potentially new bioinsecticides in field crops, we describe the fractionation of impure extracts (C8 extracts) derived from protein-rich fractions of commercial pea flour. The activity of separated fractions was determined by a flour disk antifeedant bioassay with the rice weevil [Sitophilus oryzae (L.)], an insect pest of stored products. Bioassay-guided fractionation showed that the triterpenoid saponin fractions were partly responsible for the antifeedant activity of C8 extracts. Soyasaponin I (soyasaponin Bb), isolated from peas and soybeans, and mixtures of soyasaponins, comprised of soyasaponins I-III and isolated from soybeans, were inactive antifeedants, but dehydrosoyasaponin I (the C-22 ketone derivative of soyasaponin I), a minor component found in C8 extracts, was shown to be an active component. Dehydrosoyasaponin I (soyasaponin Be) and soyasaponin VI (soyasaponin betag) coeluted under conditions of silica gel thin-layer chromatography and C18 high-performance liquid chromatography. However, dehydrosoyasaponin I could be isolated from saponin-enriched fractions with a reversed phase column of styrene/divinylbenzene operated at alkaline pH. Phospholipids of the lysolecithin type were also identified in saponin fractions of C8 extracts from peas. Three of the lysolecithins were inactive alone against rice weevils, but mixtures of these phospholipids enhanced the insecticidal activity of dehydrosoyasaponin I.
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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) | 0.000 | 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".