Metabolic Resistance in the Fall Armyworm: An Overview
Bibliographic record
Abstract
The Fall Armyworm (FAW), Spodoptera frugiperda (Smith, 1797) (Lepidoptera: Noctuidae), is one of the most important pests in the American continent and has recently become an invasive species in Africa. It’s main form of control is through the use of insecticides, however during the last 40 years, due to continuous spraying and high doses used along with FAW’s high adaptative capacity, developed resistance to different classes of chemical insecticides. One of the main mechanisms enabling resistance in the FAW is by detoxification enzymes or so-called metabolic resistance. P450s, Carboxylesterases and Glutathione-S-Transferases are the main families of enzymes believed to mediate the detoxification process. These enzymes in the FAW, although widely studied, have been difficult to generalize into patterns. This happens mainly because FAW populations can have high genetic variability within the species, as they have different biotypes meaning that they can be morphologically identical but physiologically different and consequently, enzymatic responses to toxic compounds can also differ. There are also differences due to the diversity of biomes in which S. frugiperda is found, which due to adaptations to different host plants and other abiotic factors, it’s hard to predict enzymatic responses in insecticide resistance. In this context we aimed to review the literature regarding these three main enzymes families involved in metabolic resistance in S. frugiperda, by cataloguing, analysing and summarizing these studies.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".