Gamma aminobutyrate: from intellectual curiosity to practical pest control
Bibliographic record
Abstract
The authors describe the development of gamma aminobutyrate (GABA) as a potential control agent in plant invertebrate pest systems. The evidence indicates that GABA accumulation in plants in response to biotic and abiotic stresses is mediated via the activation of glutamate decarboxylase. More applied research, based on the fact that GABA acts as an inhibitory neurotransmitter in invertebrate pests, indicates that ingested GABA disrupts nerve functioning and causes damage to oblique-banded leafroller larvae, and that walking or herbivory by tobacco budworm and oblique-banded leafroller larvae stimulate GABA accumulation in soybean and tobacco, respectively. In addition, elevated levels of endogenous GABA in genetically engineered tobacco deter feeding by tobacco budworm larvae and infestation by the northern root-knot nematode. It is concluded that genetically engineered crop species overexpressing glutamate decarboxylase and having high GABA-producing potential may be an alternative strategy to chemical pesticides for the management of invertebrate pests.Key words: gamma aminobutyrate, glutamate decarboxylase, invertebrate pests, plant defense.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".